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Alvarez-Miranda, E., & Pereira, J. (2022). A Districting Application with a Quality of Service Objective. Mathematics, 10(1), 13.
Abstract: E-commerce sales have led to a considerable increase in the demand for last-mile delivery companies, revealing several problems in their logistics processes. Among these problems, are not meeting delivery deadlines. For example, in Chile, the national consumer service (SERNAC) indicated that in 2018, late deliveries represented 23% of complaints in retail online sales and were the second most common reason for complaints. Some of the causes are incorrectly designed delivery zones because in many cases, these delivery zones do not account for the demographic growth of cities. The result is an imbalanced workload between different zones, which leads to some resources being idle while others fail to meet their workload in satisfactory conditions. The present work proposes a hybrid method for designing delivery zones with an objective based on improving the quality of express delivery services. The proposed method combines a preprocess based on the grouping of demand in areas according to the structure of the territory, a heuristic that generates multiple candidates for the distribution zones, and a mathematical model that combines the different distribution zones generated to obtain a final territorial design. To verify the applicability of the proposed method, a case study is considered based on the real situation of a Chilean courier company with low service fulfillment in its express deliveries. The results obtained from the computational experiments show the applicability of the method, highlighting the validity of the aggregation procedure and improvements in the results obtained using the hybrid method compared to the initial heuristic. The final solution improves the ability to meet the conditions associated with express deliveries, compared with the current situation, by 12 percentage points. The results also allow an indicative sample of the critical service factors of a company to be obtained, identifying the effects of possible changes in demand or service conditions
Keywords: districtin; glast-mile delivery; hybrid heuristics
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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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Alvarez-Miranda, E., Pereira, J., Torrez-Meruvia H., & Vila, M. (2021). A Hybrid Genetic Algorithm for the Simple Assembly Line Balancing Problem with a Fixed Number of Workstations. Mathematics, 9(17), 2157.
Abstract: The assembly line balancing problem is a classical optimisation problem whose objective is to assign each production task to one of the stations on the assembly line so that the total efficiency of the line is maximized. This study proposes a novel hybrid method to solve the simple version of the problem in which the number of stations is fixed, a problem known as SALBP-2. The hybrid differs from previous approaches by encoding individuals of a genetic algorithm as instances of a modified problem that contains only a subset of the solutions to the original formulation. These individuals are decoded to feasible solutions of the original problem during fitness evaluation in which the resolution of the modified problem is conducted using a dynamic programming based approach that uses new bounds to reduce its state space. Computational experiments show the efficiency of the method as it is able to obtain several new best-known solutions for some of the benchmark instances used in the literature for comparison purposes.
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Balbontin, C., Hensher, D. A., & Beck, M. J. (2022). Advanced modelling of commuter choice model and work from home during COVID-19 restrictions in Australia. Transp. Res. E-Logist. Transp. Rev., 162, 102718.
Abstract: The decision to work from home (WFH) or to commute during COVID-19 is having a major structural impact on individuals' travel, work and lifestyle. There are many possible factors influencing this non-marginal change, some of which are captured by objective variables while others are best represented by a number of underlying latent traits captured by attitudes towards WFH and the use of specific modes of transport for the commute that have a bio-security risk such as public transport (PT). We develop and implement a hybrid choice model to investigate the sources of influence, accounting for the endogenous nature of latent soft variables for workers in metropolitan areas in New South Wales and Queensland. The data was collected between September-October 2020, during a period of no lockdown and relatively minor restrictions on workplaces and public gatherings. The results show that one of the most important attributes defining the WFH loving attitude is the workplace policy towards WFH, with workers that can decide where to work having a higher probability of WFH, followed by those that are being directed to, relative to other workplace policies. The bio-security concern with using shared modes such as public transport is a key driver of WFH and choosing to commute via the safer environment of the private car.
Keywords: Working from home; Hybrid choice model; Commuting activity; COVID-19
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Contreras, J., Lopez, D., Gomez, G., & Vidal, G. (2022). Seasonal Enhancement of Nitrogen Removal on Domestic Wastewater Treatment Performance by Partially Saturated and Saturated Hybrid Constructed Wetland. Water, 14(7), 1089.
Abstract: The aim of this study is to evaluate seasonal enhancement of nitrogen removal on domestic wastewater treatment performance by partially saturated and saturated HBCWs. To achieve this, two HBCWs consisting of a vertical subsurface flow constructed wetland, followed by a horizontal subsurface flow constructed wetland (VSSF-HSSF) were evaluated. Two saturation levels were used: (a) partially saturated HB1:VSSF1 (0.6 m)-HSSF1 (0.15 m), (b) saturated HB2: VSSF2 (0.8 m)-HSSF2 (0.25 m). Each unit was planted with Schoenoplectus californicus and was operated for 297 days. The removal efficiencies in HB1 and HB2 were above 70%, 86%, 77% and 55% for chemical oxygen demand (COD), total suspended solids (TSS), nitrogen as ammonium (NH4+-N), and total nitrogen (TN), respectively. For VSSF, a higher level of saturation (from 0.6 to 0.8 m) meant a decrease of 17% in the TN removal efficiencies, and for HSSF, an increase from 0.15 to 0.25 m of saturation meant a decrease of 11 and 10% in the NH4+-N and TN removal efficiencies, respectively. Thus, the increase of saturation level in HBCWs reduces the transformation and/or removal of components of the wastewaters to be treated, particularly nitrogen. Through this research, the possibility of optimizing the transformation of nitrogen with partially saturated hybrids can be examined.
Keywords: hybrid constructed wetland; saturation level; organic matter; ammonia
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Di Genova, A., Ruz, G. A., Sagot, M. F., & Maass, A. (2018). Fast-SG: an alignment-free algorithm for hybrid assembly. GigaScience, 7(5), 15 pp.
Abstract: Background: Long-read sequencing technologies are the ultimate solution for genome repeats, allowing near reference-level reconstructions of large genomes. However, long-read de novo assembly pipelines are computationally intense and require a considerable amount of coverage, thereby hindering their broad application to the assembly of large genomes. Alternatively, hybrid assembly methods that combine short-and long-read sequencing technologies can reduce the time and cost required to produce de novo assemblies of large genomes. Results: Here, we propose a new method, called Fast-SG, that uses a new ultrafast alignment-free algorithm specifically designed for constructing a scaffolding graph using light-weight data structures. Fast-SG can construct the graph from either short or long reads. This allows the reuse of efficient algorithms designed for short-read data and permits the definition of novel modular hybrid assembly pipelines. Using comprehensive standard datasets and benchmarks, we show how Fast-SG outperforms the state-of-the-art short-read aligners when building the scaffolding graph and can be used to extract linking information from either raw or error-corrected long reads. We also show how a hybrid assembly approach using Fast-SG with shallow long-read coverage (5X) and moderate computational resources can produce long-range and accurate reconstructions of the genomes of Arabidopsis thaliana (Ler-0) and human (NA12878). Conclusions: Fast-SG opens a door to achieve accurate hybrid long-range reconstructions of large genomes with low effort, high portability, and low cost.
Keywords: hybrid assembly; genome scaffolding; alignment-free
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Navas-Fonseca, A., Burgos-Mellado, C., Gomez, J. S., Espina, E., Llanos, J., Saez, D., et al. (2023). Distributed Predictive Secondary Control With Soft Constraints for Optimal Dispatch in Hybrid AC/DC Microgrids. IEEE Trans. Smart Grid, 14(6), 4204–4218.
Abstract: Hybrid AC/DC microgrids (H-MGs) are a prominent solution for integrating distributed generation and modern AC and DC loads. However, controlling these systems is challenging as multiple electrical variables need to be controlled and coordinated. To provide flexibility to the control system, these variables can be regulated to specific values or within secure bands. This paper proposes a set of distributed model predictive control schemes for the secondary control level to control certain variables to specific values and other variables within secure pre-defined bands into H-MGs. Specifically, optimal dispatch of active and reactive power is achieved while frequency and voltages are regulated within secure bands in H-MGs. Dynamic models of AC generators, DC generators and interlinking converters along with their novel multi-objective cost functions are developed in constrained distributed predictive optimisation problems to simultaneously achieve the aforementioned objectives via information sharing. Extensive simulation work validates the performance of this proposal.
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Parrado, C., Girard, A., Simon, F., & Fuentealba, E. (2016). 2050 LCOE (Levelized Cost of Energy) projection for a hybrid PV (photovoltaic)-CSP (concentrated solar power) plant in the Atacama Desert, Chile. Energy, 94, 422–430.
Abstract: This study calculates the LCOE (Levelized Cost of Energy) on the PSDA (Atacama Solar Platform) for a solar-solar energy mix with the objective of evaluate new options for continuous energy delivery. LCOE was calculated for three 50 MW (megawatt) power plants: A PV (photovoltaic), a CSP (concentrated solar power) plant with 15 h TES (thermal energy storage) and a hybrid PV-CSP plant constituted with 20 MWp of PV and 30 MW of CSP with 15 h TES. Calculations present two scenario projections (Blue Map and Roadmap) until 2050 for each type of plant. Due to the huge solar resource available in northern Chile, the PV-CSP hybrid plant results to be a feasible option for electricity generation, as well as being effectively able to meet electricity demand profile of the mining industry present in the area. This type of energy could mitigate long-term energy costs for the heavy mining activity, as well as the country CO2 emissions. Findings point out that PV-CSP plants are a feasible option able to contribute to the continuous delivery of sustainable electricity in northern Chile. Moreover, this option can also contribute towards electricity price stabilization, thus benefiting the mining industry, as well as reducing Chile's carbon footprint. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords: LCOE; PV; CSP; Mining industry; Solar resource; Hybrid
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Pereira, J., Ritt, M., & Vasquez, O. C. (2018). A memetic algorithm for the cost-oriented robotic assembly line balancing problem. Comput. Oper. Res., 99, 249–261.
Abstract: In order to minimize costs, manufacturing companies have been relying on assembly lines for the mass production of commodity goods. Among other issues, the successful operation of an assembly line requires balancing work among the stations of the line in order to maximize its efficiency, a problem known in the literature as the assembly line balancing problem, ALBP. In this work, we consider an ALBP in which task assignment and equipment decisions are jointly considered, a problem that has been denoted as the robotic ALBP. Moreover, we focus on the case in which equipment has different costs, leading to a cost-oriented formulation. In order to solve the problem, which we denote as the cost-oriented robotic assembly line balancing problem, cRALBP, a hybrid metaheuristic is proposed. The metaheuristic embeds results obtained for two special cases of the problem within a genetic algorithm in order to obtain a memetic algorithm, applicable to the general problem. An extensive computational experiment shows the advantages of the hybrid approach and how each of the components of the algorithm contributes to the overall ability of the method to obtain good solutions. (C) 2018 Elsevier Ltd. All rights reserved.
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