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Author Averbakh, I.; Pereira, J doi  openurl
  Title Tree optimization based heuristics and metaheuristics in network construction problems Type
  Year 2021 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.  
  Volume 128 Issue Pages 105190  
  Keywords Network design; Scheduling; Network construction; Heuristics; Metaheuristics; Local search  
  Abstract We consider a recently introduced class of network construction problems where edges of a transportation network need to be constructed by a server (construction crew). The server has a constant construction speed which is much lower than its travel speed, so relocation times are negligible with respect to construction times. It is required to find a construction schedule that minimizes a non-decreasing function of the times when various connections of interest become operational. Most problems of this class are strongly NP-hard on general networks, but are often tree-efficient, that is, polynomially solvable on trees. We develop a generic local search heuristic approach and two metaheuristics (Iterated Local Search and Tabu Search) for solving tree-efficient network construction problems on general networks, and explore them computationally. Results of computational experiments indicate that the methods have excellent performance.  
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  Series Volume Series Issue Edition  
  ISSN 0305-0548 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000632975100009 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1362  
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Author Averbakh, I.; Pereira, J. pdf  doi
openurl 
  Title Lateness Minimization in Pairwise Connectivity Restoration Problems Type
  Year 2018 Publication Informs Journal On Computing Abbreviated Journal INFORMS J. Comput.  
  Volume 30 Issue 3 Pages 522-538  
  Keywords combinatorial optimization; networks: scheduling; programming: branch and bound; network restoration; network construction; integrated network design and scheduling  
  Abstract A network is given whose edges need to be constructed (or restored after a disaster). The lengths of edges represent the required construction/restoration times given available resources, and one unit of length of the network can be constructed per unit of time. All points of the network are accessible for construction at any time. For each pair of vertices, a due date is given. It is required to find a construction schedule that minimizes the maximum lateness of all pairs of vertices, where the lateness of a pair is the difference between the time when the pair becomes connected by an already constructed path and the pair's due date. We introduce the problem and analyze its structural properties, present a mixed-integer linear programming formulation, develop a number of lower bounds that are integrated in a branch-and-bound algorithm, and discuss results of computational experiments both for instances based on randomly generated networks and for instances based on 2010 Chilean earthquake data.  
  Address [Averbakh, Igor] Univ Toronto Scarborough, Dept Management, Toronto, ON M1C 1A4, Canada, Email: averbakh@utsc.uturonto.ca;  
  Corporate Author Thesis  
  Publisher Informs Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1091-9856 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000449096000008 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 924  
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Author Azar, M.; Carrasco, R.A.; Mondschein, S. doi  openurl
  Title Dealing with Uncertain Surgery Times in Operating Room Scheduling Type
  Year 2022 Publication European Journal of Operational Research Abbreviated Journal Eur. J. Oper. Res.  
  Volume 299 Issue 1 Pages 377-394  
  Keywords Scheduling, OR in health services, Operating Room Scheduling, Scheduling under Uncertainty  
  Abstract The operating theater is one of the most expensive units in the hospital, representing up to 40% of the total expenses. Because of its importance, the operating room scheduling problem has been addressed from many different perspectives since the early 1960s. One of the main difficulties that

has reduced the applicability of the current results is the high variability in surgery duration, making schedule recommendations hard to implement.

In this work, we propose a time-indexed scheduling formulation to solve the operational problem. Our main contribution is that we propose the use of chance constraints related to the surgery duration's probability distribution for each surgeon to improve the scheduling performance. We show how to implement these chance constraints as linear ones in our time-indexed formulation, enhancing the performance of the resulting schedules signifi cantly.

Through data analysis of real historical instances, we develop specific constraints that improve the schedule, reducing the need for overtime without affecting the utilization signifi cantly. Furthermore, these constraints give the operating room manager the possibility of balancing overtime and utilization through a tunning parameter in our formulation. Finally, through simulations and the use of real instances, we report the performance for four different metrics, showing the importance of using historical data to get the right balance between the utilization and overtime.
 
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  ISSN 0377-2217 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000743256000003 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1448  
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Author Barrera, J.; Carrasco, R.A.; Mondschein, S.; Canessa, G.; Rojas-Zalazar, D. doi  openurl
  Title Operating room scheduling under waiting time constraints: the Chilean GES plan Type
  Year 2020 Publication Annals Of Operations Research Abbreviated Journal Ann. Oper. Res.  
  Volume 286 Issue 1-2 Pages 501-527  
  Keywords Scheduling; Operating theater; Operating room scheduling  
  Abstract In 2000, Chile introduced profound health reforms to achieve a more equitable and fairer system (GES plan). The reforms established a maximum waiting time between diagnosis and treatment for a set of diseases, described as an opportunity guarantee within the reform. If the maximum waiting time is exceeded, the patient is referred to another (private) facility and receives a voucher to cover the additional expenses. This voucher is paid by the health provider that had to do the procedure, which generally is a public hospital. In general, this reform has improved the service for patients with GES pathologies at the expense of patients with non-GES pathologies. These new conditions create a complicated planning scenario for hospitals, in which the hospital's OR Manager must balance the fulfillment of these opportunity guarantees and the timely service of patients not covered by the guarantee. With the collaboration of the Instituto de Neurocirugia, in Santiago, Chile, we developed a mathematical model based on stochastic dynamic programming to schedule surgeries in order to minimize the cost of referrals to the private sector. Given the large size of the state space, we developed an heuristic to compute good solutions in reasonable time and analyzed its performance. Our experimental results, with both simulated and real data, show that our algorithm performs close to optimum and improves upon the current practice. When we compared the results of our heuristic against those obtained by the hospital's OR manager in a simulation setting with real data, we reduced the overtime from occurring 21% of the time to zero, and the non-GES average waiting list's length from 71 to 58 patients, without worsening the average throughput.  
  Address [Barrera, Javiera; Carrasco, Rodrigo A.; Mondschein, Susana; Canessa, Gianpiero] Univ Adolfo Ibanez, Fac Engn & Sci, Santiago, Chile, Email: javiera.barrera@uai.cl;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0254-5330 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000511564300021 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 1104  
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Author Beya-Marshall, V.; Arcos, E.; Seguel, O.; Galleguillos, M.; Kremer, C. doi  openurl
  Title Optimal irrigation management for avocado (cv. 'Hass') trees by monitoring soil water content and plant water status Type
  Year 2022 Publication Agricultural Water Management Abbreviated Journal Agric. Water Manag.  
  Volume 271 Issue Pages 107794  
  Keywords Water productivity; Stem water potential; Baseline; Frequency domain reflectometry; Irrigation scheduling; Yield; Water scarcity  
  Abstract Irrigation scheduling based on soil water content (Ow) sensors requires that Ow be maintained within a range (management lines) that is optimal for plant growth. The lower limit or “breaking point ” is determined following the soil water content dynamics on the transition of a rapid rate of depletion to a slower, under similar reference evapotranspiration. Although this criterion is practical, its implementation should be validated with plant water status measurement that contemplate weather condition, such as stem water potential “non-stressed ” baseline (Tx as a function of vapor-pressure deficit (VPD) in Ow conditions that do not limit yield). A study was con-ducted on a mature cv. 'Hass' avocado orchard in Central Chile during two seasons. There were 5 irrigation treatments: T1, Control; T2 and T3 with 29% less and 25% more of what was applied in T1, respectively; T4 and T5 same as Control until first and second fruit drop abscission, respectively, and then with 29% less. T1 trees were irrigated using a continuous frequency domain reflectometry (FDR) probe to maintain the root zone be-tween field capacity and the breaking point. There was biweekly monitoring of the Ow prior to irrigation, Tx and VPD. The Tx decline proportional to the intensity and the timing of water restriction; however, no treatment affected the crop load in either season. T2 did not show significant detrimental in fruit size, production and maturation, despite that frequently reached water content levels at the limit of the breaking point, and showed lower levels of stem water potential than Control, being the treatment with the highest water productivity. The results confirm that breaking point is an effective criterion to establish irrigation management. Additionally, when comparing the baseline for our non-stressed trees with a baseline from full irrigation treatments obtained from the literature, 30% water savings were achieved.  
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  ISSN 0378-3774 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000831063900003 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1615  
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Author Carrasco, R.A.; Iyengar, G.; Stein, C. pdf  doi
openurl 
  Title Resource cost aware scheduling Type
  Year 2018 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.  
  Volume 269 Issue 2 Pages 621-632  
  Keywords Scheduling; Approximation algorithms; Resource aware scheduling; Speed-scaling  
  Abstract We are interested in the scheduling problem where there are several different resources that determine the speed at which a job runs and we pay depending on the amount of each resource that we use. This work is an extension of the resource dependent job processing time problem and the energy aware scheduling problems. We develop a new constant factor approximation algorithm for resource cost aware scheduling problems: the objective is to minimize the sum of the total cost of resources and the total weighted completion time in the one machine non-preemptive setting, allowing for arbitrary precedence constraints and release dates. Our algorithm handles general job-dependent resource cost functions. We also analyze the practical performance of our algorithms, showing that it is significantly superior to the theoretical bounds and in fact it is very close to optimal. The analysis is done using simulations and real instances, which are left publicly available for future benchmarks. We also present additional heuristic improvements and we study their performance in other settings. (C) 2018 Elsevier B.V. All rights reserved.  
  Address [Carrasco, Rodrigo A.] Univ Adolfo Ibanez, Fac Sci & Engn, Santiago, Chile, Email: rax@uai.cl;  
  Corporate Author Thesis  
  Publisher Elsevier Science Bv Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0377-2217 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000432502600016 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 871  
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Author Cohen, Y.M.; Keskinocak, P.; Pereira, J. doi  openurl
  Title A note on the flowtime network restoration problem Type
  Year 2021 Publication IISE Transactions Abbreviated Journal IISE Trans.  
  Volume 53 Issue 12 Pages 1351-1352  
  Keywords Scheduling; network construction planning; emergency restoration operations; deliveryman problem; traveling repairman problem  
  Abstract The flowtime network restoration problem was introduced by Averbakh and Pereira (2012) who presented a Minimum Spanning Tree heuristic, two local search procedures, and an exact branch-and-bound algorithm. This note corrects the computational results in Averbakh and Pereira (2012).  
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  ISSN 2472-5854 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000617722200001 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1343  
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Author Espinoza, D.; Goycoolea, M.; Moreno, E.; Newman, A. pdf  doi
openurl 
  Title MineLib: a library of open pit mining problems Type
  Year 2013 Publication Annals Of Operations Research Abbreviated Journal Ann. Oper. Res.  
  Volume 206 Issue 1 Pages 93-114  
  Keywords Mine scheduling; Mine planning; Open pit production scheduling; Surface mine production scheduling; Problem libraries; Open pit mining library  
  Abstract Similar to the mixed-integer programming library (MIPLIB), we present a library of publicly available test problem instances for three classical types of open pit mining problems: the ultimate pit limit problem and two variants of open pit production scheduling problems. The ultimate pit limit problem determines a set of notional three-dimensional blocks containing ore and/or waste material to extract to maximize value subject to geospatial precedence constraints. Open pit production scheduling problems seek to determine when, if ever, a block is extracted from an open pit mine. A typical objective is to maximize the net present value of the extracted ore; constraints include precedence and upper bounds on operational resource usage. Extensions of this problem can include (i) lower bounds on operational resource usage, (ii) the determination of whether a block is sent to a waste dump, i.e., discarded, or to a processing plant, i.e., to a facility that derives salable mineral from the block, (iii) average grade constraints at the processing plant, and (iv) inventories of extracted but unprocessed material. Although open pit mining problems have appeared in academic literature dating back to the 1960s, no standard representations exist, and there are no commonly available corresponding data sets. We describe some representative open pit mining problems, briefly mention related literature, and provide a library consisting of mathematical models and sets of instances, available on the Internet. We conclude with directions for use of this newly established mining library. The library serves not only as a suggestion of standard expressions of and available data for open pit mining problems, but also as encouragement for the development of increasingly sophisticated algorithms.  
  Address [Espinoza, Daniel] Univ Chile, Dept Ind Engn, Santiago Ctr, Santiago, Chile, Email: daespino@dii.uchile.cl;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0254-5330 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000320694000006 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 290  
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Author Homem-de-Mello, T.; Kong, Q.X.; Godoy-Barba, R. doi  openurl
  Title A Simulation Optimization Approach for the Appointment Scheduling Problem with Decision-Dependent Uncertainties Type
  Year 2022 Publication Informs Journal On Computing Abbreviated Journal INFORMS J. Comput.  
  Volume Early Access Issue Pages  
  Keywords stochastic optimization; decision-dependent uncertainty; appointment scheduling; no-show; healthcare management  
  Abstract The appointment scheduling problem (ASP) studies how to manage patient arrivals to a healthcare system to improve system performance. An important challenge occurs when some patients may not show up for an appointment. Although the ASP is well studied in the literature, the vast majority of the existing work does not consider the well-observed phenomenon that patient no-show is influenced by the appointment time, the usual decision variable in the ASP. This paper studies the ASP with random service time (exogenous uncertainty) with known distribution and patient decision-dependent no-show behavior (endogenous uncertainty). This problem belongs to the class of stochastic optimization with decision-dependent uncertainties. Such problems are notoriously difficult as they are typically nonconvex. We propose a stochastic projected gradient path (SPGP) method to solve the problem, which requires the development of a gradient estimator of the objective function-a nontrivial task, as the literature on gradient-based optimization algorithms for problems with decision-dependent uncertainty is very scarce and unsuitable for our model. Our method can solve the ASP problem under arbitrarily smooth show-up probability functions. We present solutions under different patterns of no-show behavior and demonstrate that breaking the assumption of constant show-up probability substantially changes the scheduling solutions. We conduct numerical experiments in a variety of settings to compare our results with those obtained with a distributionally robust optimization method developed in the literature. The cost reduction obtained with our method, which we call the value of distribution information, can be interpreted as how much the system performance can be improved by knowing the distribution of the service times, compared to not knowing it. We observe that the value of distribution information is up to 31% of the baseline cost, and that such value is higher when the system is crowded or/and the waiting time cost is relatively high.

Summary of Contribution: This paper studies an appointment scheduling problem under time-dependent patient no-show behavior, a situation commonly observed in practice. The problem belongs to the class of stochastic optimization problems with decision-dependent uncertainties in the operations research literature. Such problems are notoriously difficult to solve as a result of the lack of convexity, and the present case requires different techniques because of the presence of continuous distributions for the service times. A stochastic projected gradient path method, which includes the development of specialized techniques to estimate the gradient of the objective function, is proposed to solve the problem. For problems with a similar structure, the algorithm can be applied once the gradient estimator of the objective function is obtained. Extensive numerical studies are presented to demonstrate the quality of the solutions, the importance of modeling time-dependent no-shows in appointment scheduling, and the value of using distribution information about the service times.
 
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  Series Volume Series Issue Edition  
  ISSN 1091-9856 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000829089300001 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1611  
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Author Letelier, O.R.; Clautiaux, F.; Sadykov, R. doi  openurl
  Title Bin Packing Problem with Time Lags Type
  Year 2022 Publication Informs Journal On Computing Abbreviated Journal INFORMS J. Comput.  
  Volume Early Access Issue Pages  
  Keywords integer programming; algorithms; cutting planes; branch and bound; production-scheduling; cutting stock; relaxation  
  Abstract We introduce and motivate several variants of the bin packing problem where bins are assigned to time slots, and minimum and maximum lags are required between some pairs of items. We suggest two integer programming formulations for the general problem: a compact one and a stronger formulation with an exponential number of variables and constraints. We propose a branch-cut-and-price approach that exploits the latter formulation. For this purpose, we devise separation algorithms based on a mathematical characterization of feasible assignments for two important special cases of the problem: when the number of possible bins available at each period is infinite and when this number is limited to one and time lags are nonnegative. Computational experiments are reported for instances inspired from a real-case application of chemical treatment planning in vineyards, as well as for literature instances for special cases of the problem. The experimental results show the efficiency of our branch-cutand-price approach, as it outperforms the compact formulation on newly proposed instances and is able to obtain improved lower and upper bounds for literature instances. Summary of Contribution: The paper considers a new variant of the bin packing problem, which is one of the most important problems in operations research. A motivation for introducing this variant is given, as well as a real-life application. We present a novel and original exact branch-cut-and-price algorithm for the problem. We implement this algorithm, and we present the results of extensive computational experiments. The results show a very good performance of our algorithm. We give several research directions that can be followed by subsequent researchers to extend our contribution to more complex and generic problems.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1091-9856 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000804384300001 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1588  
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Author Letelier, O.R.; Espinoza, D.; Goycoolea, M.; Moreno, E.; Munoz, G. doi  openurl
  Title Production Scheduling for Strategic Open Pit Mine Planning: A Mixed-Integer Programming Approach Type
  Year 2020 Publication Operations Research Abbreviated Journal Oper. Res.  
  Volume 68 Issue 5 Pages 1425-1444  
  Keywords open pit mining; production scheduling; column generation; heuristics; cutting planes; integer programming applications  
  Abstract Given a discretized representation of an ore body known as a block model, the open pit mining production scheduling problem that we consider consists of defining which blocks to extract, when to extract them, and how or whether to process them, in such a way as to comply with operational constraints and maximize net present value. Although it has been established that this problem can be modeled with mixed-integer programming, the number of blocks used to represent real-world mines (millions) has made solving large instances nearly impossible in practice. In this article, we introduce a new methodology for tackling this problem and conduct computational tests using real problem sets ranging in size from 20,000 to 5,000,000 blocks and spanning 20 to 50 time periods. We consider both direct block scheduling and bench-phase scheduling problems, with capacity, blending, and minimum production constraints. Using new preprocessing and cutting planes techniques, we are able to reduce the linear programming relaxation value by up to 33%, depending on the instance. Then, using new heuristics, we are able to compute feasible solutions with an average gap of 1.52% relative to the previously computed bound. Moreover, after four hours of running a customized branch-and-bound algorithm on the problems with larger gaps, we are able to further reduce the average from 1.52% to 0.71%.  
  Address [Rivera Letelier, Orlando] Univ Adolfo Ibanez, Doctoral Program Ind Engn & Operat Res, Santiago 7941169, Chile, Email: orlando.rivera@uai.cl;  
  Corporate Author Thesis  
  Publisher Informs Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0030-364x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000574409100008 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1250  
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Author Mejia, G.; Pereira, J. doi  openurl
  Title Multiobjective scheduling algorithm for flexible manufacturing systems with Petri nets Type
  Year 2020 Publication Journal Of Manufacturing Systems Abbreviated Journal J. Manuf. Syst.  
  Volume 54 Issue Pages 272-284  
  Keywords Machine scheduling; Multi-objective optimization; Petri nets  
  Abstract In this work, we focus on general multi-objective scheduling problems that can be modeled using a Petri net framework. Due to their generality, Petri nets are a useful abstraction that captures multiple characteristics of real-life processes. To provide a general solution procedure for the abstraction, we propose three alternative approaches using an indirect scheme to represent the solution: (1) a genetic algorithm that combines two objectives through a weighted fitness function, (2) a non dominated sorting genetic algorithm (NSGA-II) that explicitly addresses the multi-objective nature of the problem and (3) a multi-objective local search approach that simultaneously explores multiple candidate solutions. These algorithms are tested in an extensive computational experiment showing the applicability of this general framework to obtain quality solutions.  
  Address [Mejia, Gonzalo] Univ La Sabana, Fac Engn, Campus Puente del Comun, Chia, Colombia, Email: gonzalo.mejia@unisabana.edu.co;  
  Corporate Author Thesis  
  Publisher Elsevier Sci Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0278-6125 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000521511500021 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 1154  
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Author Ogunmodede, O.; Lamas, P.; Brickey, A.; Bogin, G.; Newman, A. doi  openurl
  Title Underground production scheduling with ventilation and refrigeration considerations Type
  Year 2022 Publication Optimization And Engineering Abbreviated Journal Optim. Eng.  
  Volume Early Access Issue Pages  
  Keywords Underground mine scheduling; Integer programming applications; Resource-constrained project scheduling; Ventilation; Diesel equipment; Refrigeration  
  Abstract Underground mine production scheduling determines when, if ever, activities associated with the extraction of ore should be executed. The accumulation of heat in the mine where operators are working is a major concern. At the time of this writing, production scheduling and ventilation decisions are not made in concert. Correspondingly, heat limitations are largely ignored. Our mixed-integer program maximizes net present value subject to constraints on precedence, and mill and extraction capacities with the consideration of heat using thermodynamic principles, while affording the option of activating refrigeration to mitigate heat accumulation. In seconds to hours, depending on the problem size (up to thousands of activities and 900 daily time periods), a corresponding methodology that exploits the mathematical problem structure provides schedules that maintain a safe working environment for mine operators; optimality gaps are no more than 15% and average less than half that for otherwise-intractable instances.  
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  Series Volume Series Issue Edition  
  ISSN 1389-4420 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000741919400001 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1519  
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Author Osorio-Valenzuela, L.; Pereira, J.; Quezada, F.; Vasquez, O.C. doi  openurl
  Title Minimizing the number of machines with limited workload capacity for scheduling jobs with interval constraints Type
  Year 2019 Publication Applied Mathematical Modelling Abbreviated Journal Appl. Math. Model.  
  Volume 74 Issue Pages 512-527  
  Keywords Scheduling; Parallel machines; Interval and workload constraints; Branch-and-price  
  Abstract In this paper, we consider a parallel machine scheduling problem in which machines have a limited workload capacity and jobs have deadlines and release dates. The problem is motivated by the operation of energy storage management systems for microgrids under emergency conditions and generalizes some problems that have already been studied in the literature for their theoretical value. In this work, we propose heuristic and exact algorithms to solve the problem. The heuristics are adaptations of classical bin packing heuristics in which additional conditions on the feasibility of a solution are imposed, whereas the exact method is a branch-and-price approach. The results show that the branch-andprice approach is able to optimally solve random instances with up to 250 jobs within a time limit of one hour, while the heuristic procedures provide near optimal solution within reduced running times. Finally, we also provide additional complexity results for a special case of the problem. (C) 2019 Elsevier Inc. All rights reserved.  
  Address [Osorio-Valenzuela, Luis] Univ Santiago Chile, Elect Engn Dept, Santiago, Chile, Email: luis.osoriov@usach.cl;  
  Corporate Author Thesis  
  Publisher Elsevier Science Inc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0307-904x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000474317800031 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 1013  
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Author Pereira, J. pdf  doi
openurl 
  Title The robust (minmax regret) single machine scheduling with interval processing times and total weighted completion time objective Type
  Year 2016 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.  
  Volume 66 Issue Pages 141-152  
  Keywords Scheduling; Single machine; Uncertainty; Robust optimization; Branch-and-bound  
  Abstract Single machine scheduling is a classical optimization problem that depicts multiple real life systems in which a single resource (the machine) represents the whole system or the bottleneck operation of the system. In this paper we consider the problem under a weighted completion time performance metric in which the processing time of the tasks to perform (the jobs) are uncertain, but can only take values from closed intervals. The objective is then to find a solution that minimizes the maximum absolute regret for any possible realization of the processing times. We present an exact branch-and-bound method to solve the problem, and conduct a computational experiment to ascertain the possibilities and limitations of the proposed method. The results show that the algorithm is able to optimally solve instances of moderate size (25-40 jobs depending on the characteristics of the instance). (c) 2015 Elsevier Ltd. All rights reserved.  
  Address [Pereira, Jordi] Univ Adolfo Ibanez, Fac Sci & Engn, Vina Del Mar, Chile, Email: jorge.pereira@uai.cl  
  Corporate Author Thesis  
  Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0305-0548 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000366779900013 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 558  
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Author Pereira, J.; Vasquez, O.C. pdf  doi
openurl 
  Title The single machine weighted mean squared deviation problem Type
  Year 2017 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.  
  Volume 261 Issue 2 Pages 515-529  
  Keywords Scheduling; Single machine; JIT; Branch-and-cut; Dominance properties  
  Abstract This paper studies a single machine problem related to the just-In-Time (JIT) production objective in which the goal is to minimize the sum of weighted mean squared deviation of the completion times with respect to a common due date. In order to solve the problem, several structural and dominance properties of the optimal solution are investigated. These properties are then integrated within a branch and-cut approach to solve a time-indexed formulation of the problem. The results of a computational experiment with the proposed algorithm show that the method is able to optimally solve instances with up to 300 jobs within reduced running times, improving other integer programming approaches. (C) 2017 Elsevier B.V. All rights reserved.  
  Address [Pereira, Jordi] Univ Adolfo Ibanez, Dept Engn & Sci, Av Padre Hurtado 750,Off C216, Vina Del Mar, Chile, Email: jorge.pereira@uai.cl;  
  Corporate Author Thesis  
  Publisher Elsevier Science Bv Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0377-2217 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000401206300009 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 730  
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Author Reus, L.; Belbeze, M.; Feddersen, H.; Rubio, E. doi  openurl
  Title Extraction Planning Under Capacity Uncertainty at the Chuquicamata Underground Mine Type
  Year 2018 Publication Interfaces Abbreviated Journal Interfaces  
  Volume 48 Issue 6 Pages 543-555  
  Keywords underground mine extraction scheduling; operational uncertainty management; stochastic programming applications; long-term mine planning  
  Abstract We propose an extraction schedule for the Chuquicamata underground copper mine in Chile. The schedule maximizes profits while adhering to all operational and geomechanical requirements involved in proper removal of the material. We include extraction capacity uncertainties due to failure in equipment, specifically to the overland conveyor, which we find to be the most critical component in the extraction process. First we present the extraction plan based on a deterministic model, which does not assume uncertainty in the extraction capacity and represents the solution that the mine can implement without using the results of this study. Then we extend this model to a stochastic setting by generating different scenarios for capacity values in subsequent periods. We construct a multistage model that handles economic downside risk arising from this uncertainty by penalizing plans that deviate from an ex ante profit target in one or more scenarios. Simulation results show that a stochastic-based solution can achieve the same expected profits as the deterministic-based solution. However, the earnings of the stochastic-based solution average 5% more for scenarios in which earnings are below the 10th percentile. If we choose a target 2% below the expected profit obtained by the deterministic-based solution, this average increases from 5% to 9%.  
  Address [Reus, Lorenzo; Belbeze, Mathias; Feddersen, Hans] Adolfo Ibanez Univ, Dept Engn & Sci, Santiago 7910000, Chile, Email: lorenzo.reus@uai.cl;  
  Corporate Author Thesis  
  Publisher Informs Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0092-2102 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000454513500005 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 967  
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Author Yuraszeck, F.; Mejia, G.; Pereira, J.; Vila, M. doi  openurl
  Title A Novel Constraint Programming Decomposition Approach for the Total Flow Time Fixed Group Shop Scheduling Problem Type
  Year 2022 Publication Mathematics Abbreviated Journal Mathematics  
  Volume 10 Issue 3 Pages 329  
  Keywords scheduling; fixed group shop; group shop; constraint programming  
  Abstract This work addresses a particular case of the group shop scheduling problem (GSSP) which will be denoted as the fixed group shop scheduling problem (FGSSP). In a FGSSP, job operations are divided into stages and each stage has a set of machines associated to it which are not shared with the other stages. All jobs go through all the stages in a specific order, where the operations of the job at each stage need to be finished before the job advances to the following stage, but operations within a stage can be performed in any order. This setting is common in companies such as leaf spring manufacturers and other automotive companies. To solve the problem, we propose a novel heuristic procedure that combines a decomposition approach with a constraint programming (CP) solver and a restart mechanism both to avoid local optima and to diversify the search. The performance of our approach was tested on instances derived from other scheduling problems that the FGSSP subsumes, considering both the cases with and without anticipatory sequence-dependent setup times. The results of the proposed algorithm are compared with off-the-shelf CP and mixed integer linear programming (MILP) methods as well as with the lower bounds derived from the study of the problem. The experiments show that the proposed heuristic algorithm outperforms the other methods, specially on large-size instances with improvements of over 10% on average.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2227-7390 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000756126100001 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1549  
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Author Yushimito, W.F.; Ban, X.G.; Holguin-Veras, J. pdf  doi
openurl 
  Title Correcting the Market Failure in Work Trips with Work Rescheduling: An Analysis Using Bi-level Models for the Firm-workers Interplay Type
  Year 2015 Publication Networks & Spatial Economics Abbreviated Journal Netw Spat. Econ.  
  Volume 15 Issue 3 Pages 883-915  
  Keywords Peak congestion; Rescheduling of work; Market failure; Bi-level models; Stackelberg; Dynamic traffic assignment  
  Abstract Compulsory trips (e.g., work trips) contribute with the major part of the congestion in the morning peak. It also prevents the society to reach a social optimum (the solution that maximizes welfare) because the presence of the private utility of one the agents (the firm), acting as a dominant agent, does not account for the additional costs imposed in their workers (congestion) as well as the costs imposed to the rest of the society (i.e., congestion, pollution). In this paper, a study of a strategy to influence the demand generator by relaxing the arrival constraints is presented. Bi-level programming models are used to investigate the equilibrium reached from the firm-workers interplay which helps to explain how the market failure arises. The evaluation includes the use of incentives to induce the shift to less congested periods and the case of the social system optimum in which a planner objective is incorporated as a third agent usually seeking to improve social welfare (improve productivity of the firm while at the same time reduce the total system travel time). The later is used to show that it is possible to provide a more efficient solution which better off society. A numerical example is used to (1) show the nature of the market failure, (2) evaluate the social system optimum, and (3) show how a congestion tax or an optimal incentive can help to correct the market failure. The results also corroborate that these mechanisms are more likely to be more efficient when firms face little production effects on time and workers do not high opportunity costs for starting at off peak periods.  
  Address [Yushimito, Wilfredo F.] Univ Adolfo Ibanez, Dept Sci & Engn, Vina Del Mar, Chile, Email: wilfredo.yushimito@uai.cl;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1566-113x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000364529500023 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 622  
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