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Alvarez-Miranda, E., Chace, S., & Pereira, J. (2021). Assembly line balancing with parallel workstations. Int. J. Prod. Res., 59(21), 6486–6506.
Abstract: The simple assembly line balancing problem (SALBP) considers work division among different workstations of a serially arranged assembly process to maximise its efficiency under workload (cumulative) and technological (precedence) constraints. In this work, we consider a variant of the SALBP which allows parallel workstations. To study the effect of parallel stations, we propose a new problem (the parallel station assembly line balancing problem or PSALBP) in which the objective is to minimise the number of parallel stations required to obtain the maximum theoretical efficiency of the assembly process. We study the complexity of the problem and identify a polynomially solvable case. This result is then used as a building block for the development of a heuristic solution procedure. Finally, we carry out a computational experiment to identify the characteristics of assembly lines that may benefit from station paralleling and to evaluate the performance of the proposed heuristic.
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Bitran, G., & Mondschein, S. (2015). Why individualized contact policies are critical in the mass affluent market. Acad.-Rev. Latinoam. Adm., 28(2), 251–272.
Abstract: Purpose – The purpose of this paper is to study the optimal contact policies for customers that belong to the mass affluent market. Design/methodology/approach – The authors formulate a stochastic dynamic programming model to determine the optimal frequency of contacts in order to maximize the expected return of the company. Findings – The authors show that personalized marketing strategies provide a competitive advantage to companies that contact their customers directly through, for example, phone calls or meetings. The authors show that a threshold policy is only optimal for customers with increasing sensitivity to contact. In all other cases, optimal policies might have a less intuitive structure. The authors also study the importance of the size of the customer database and determine the optimal maximum recency when maintenance costs are present. Practical implications – Contact policies should be tailored for each company/industry individually, due to their sensitivity to customers' purchasing behavior.
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Mondschein, S., Yankovic, N., & Matus, O. (2021). Age-dependent optimal policies for hepatitis C virus treatment. Int. Trans. Oper. Res., 28(6), 3303–3329.
Abstract: In recent years, highly effective treatments for hepatitis C virus (HCV) have become available. However, high prices of new treatments call for a careful policy evaluation when considering economic constraints. Although the current medical advice is to administer the new therapies to all patients, economic and capacity constraints require an efficient allocation of these scarce resources. We use stochastic dynamic programming to determine the optimal policy for prescribing the new treatment based on the age and disease progression of the patient. We show that, in a simplified version of the model, new drugs should be administered to patients at a given level of fibrosis if they are within prespecified age limits; otherwise, a conservative approach of closely monitoring the evolution of the patient should be followed. We use a cohort of Spanish patients to study the optimal policy regarding costs and health indicators. For this purpose, we compare the performance of the optimal policy against a liberal policy of treating all sick patients. In this analysis, we achieve similar results in terms of the number of transplants, HCV-related deaths, and quality of adjusted life years, with a significant reduction in overall expenditure. Furthermore, the budget required during the first year of implementation when using the proposed methodology is only 12% of that when administering the treatment to all patients at once. Finally, we propose a method to prioritize patients when there is a shortage (surplus) in the annual budget constraint and, therefore, some recommended treatments must be postponed (added).
Keywords: dynamic programming; public health; hepatitis C virus
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Navarro, A., Favereau, M., Lorca, A., Olivares, D., & Negrete-Pincetic, M. (2024). Medium-term stochastic hydrothermal scheduling with short-term operational effects for large-scale power and water networks. Appl. Energy, 358, 122554.
Abstract: The high integration of variable renewable sources in electric power systems entails a series of challenges inherent to their intrinsic variability. A critical challenge is to correctly value the water available in reservoirs in hydrothermal systems, considering the flexibility that it provides. In this context, this paper proposes a medium -term multistage stochastic optimization model for the hydrothermal scheduling problem solved with the stochastic dual dynamic programming algorithm. The proposed model includes operational constraints and simplified mathematical expressions of relevant operational effects that allow more informed assessment of the water value by considering, among others, the flexibility necessary for the operation of the system. In addition, the hydrological uncertainty in the model is represented by a vector autoregressive process, which allows capturing spatio-temporal correlations between the different hydro inflows. A calibration method for the simplified mathematical expressions of operational effects is also proposed, which allows a detailed shortterm operational model to be correctly linked to the proposed medium -term linear model. Through extensive experiments for the Chilean power system, the results show that the difference between the expected operating costs of the proposed medium -term model, and the costs obtained through a detailed short-term operational model was only 0.1%, in contrast to the 9.3% difference obtained when a simpler base model is employed. This shows the effectiveness of the proposed approach. Further, this difference is also reflected in the estimation of the water value, which is critical in water shortage situations.
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Pereira, J. (2016). Procedures for the bin packing problem with precedence constraints. Eur. J. Oper. Res., 250(3), 794–806.
Abstract: The bin packing problem with precedence constraints (BPP-P) is a recently proposed variation of the classical bin packing problem (BPP), which corresponds to a basic model featuring many underlying characteristics of several scheduling and assembly line balancing problems. The formulation builds upon the BPP by incorporating precedence constraints among items, which force successor items to be packed into later bins than their predecessors. In this paper we propose a dynamic programming based heuristic, and a modified exact enumeration procedure to solve the problem. These methods make use of several new lower bounds and dominance rules tailored for the problem in hand. The results of a computational experiment show the effectiveness of the proposed methods, which are able to close all of the previous open instances from the benchmark instance set within very reduced running times. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
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Pereira, J., & Ritt, M. (2023). Exact and heuristic methods for a workload allocation problem with chain precedence constraints. Eur. J. Oper. Res., 309(1), 387–398.
Abstract: Industrial manufacturing is often organized in assembly lines where a product is assembled on a se-quence of stations, each of which executes some of the assembly tasks. A line is balanced if the maximum total execution time of any station is minimal. Commonly, the task execution order is constrained by precedences, and task execution times are independent of the station performing the task. Here, we con -sider a recent variation, called the “(Calzedonia) Workload Allocation Problem” (WAP), where the prece-dences form a chain, and the execution time of a task depends on the worker executing it. This problem was recently proposed by Battarra et al. (2020) and it is a special case of the Assembly Line Worker As-signment and Balancing Problem Miralles et al. (2007) where precedence relations are arbitrary. In this paper we consider the computational complexity of the problem and prove its NP-hardness. To solve the problem, we provide different lower bounds and exact and heuristic procedures. The performance of the proposed methods is tested on previously proposed instances and on new, larger instances with the same characteristics. The results show that the proposed methods can solve instances with up to about 40 0 0 tasks and 29 workers, doubling the size of the instances that previously could be solved to optimality.
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Pereira, J., & Ritt, M. (2022). A note on “Algorithms for the Calzedonia workload allocation problem”. J. Oper. Res. Soc., 73(6), 1420–1422.
Abstract: Battarra et al. recently proposed a novel assembly line balancing problem with applications to the apparel industry, where the tasks are performed in a fixed order. To solve the problem, one has to assign workers and tasks to the workstations with the objective of maximising the throughput of the assembly line. In this paper, we provide dynamic programming formulations for the general problem and some special cases. We then use these formulations to develop an exact solution approach that optimally solves the instances in Battarra et al. within seconds.
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Reus, L., Pagnoncelli, B., & Armstrong, M. (2019). Better management of production incidents in mining using multistage stochastic optimization. Resour. Policy, 63, 13 pp.
Abstract: Among the many sources of uncertainty in mining are production incidents: these can be strikes, environmental issues, accidents, or any kind of event that disrupts production. In this work, we present a strategic mine planning model that takes into account these types of incidents, as well as random prices. When confronted by production difficulties, mines which have contracts to supply customers have a range of flexibility options including buying on the spot market, or taking material from a stockpile if they have one. Earlier work on this subject was limited in that the optimization could only be carried out for a few stages (up to 5 years) and in that it only analyzed the risk-neutral case. By using decomposition schemes, we are now able to solve large-scale versions of the model efficiently, with a horizon of up to 15 years. We consider decision trees with up to 615 scenarios and implement risk aversion using Conditional Value-at-Risk, thereby detecting its effect on the optimal policy. The results provide a “roadmap” for mine management as to optimal decisions, taking future possibilities into account. We present extensive numerical results using the new sddp.jl library, written in the Julia language, and discuss policy implications of our findings.
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