Hybrid metaheuristics to solve a multiproduct two‐stage capacitated facility location problem

Mauri, Geraldo Regis; Biajoli, Fabrício Lacerda; Rabello, Rômulo Louzada; Chaves, Antônio Augusto; Ribeiro, Glaydston Mattos; Lorena, Luiz Antônio Nogueira

doi:10.1111/itor.12930

Cited by 10 publications

(4 citation statements)

References 36 publications

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“…This study is different from other studies, which assume that transportation costs are constant [5][6][7][8][9][10][11][12]. Conversely, the transportation costs in this study are not constant but a piecewise linear function.…”

Section: Introductionmentioning

confidence: 69%

Developing Supply Chain Network With Piecewise Linear Transportation Cost for a Small-and-Medium Enterprise (Sme) in Cilegon

Kurniawan

Irman

Gunawan

et al. 2023

Majalah Ilmiah Pengkajian Industri

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This study proposed a supply chain network for determining suppliers’ location in which the transportation costs are a piecewise linear function. The supply chain network consists of a production facility, suppliers, and customers. These types of costs are found in the fields of transportation, logistics, and purchasing discount. First, the supply chain network is formulated as the mixed-integer non-linear programming (MINLP) because piecewise linear transportation cost makes the model non-linear. Then, the model is transformed into a mixed-integer programming (MIP) model using the convex-combination method to overcome this nonlinearity. The model was used for solving the problem faced by a small and medium enterprise (SME) in Cilegon. The MIP was solved using the CPLEX software. Sensitivity analysis was carried to provide the SME with several alternatives in handling the suppliers’ location problem

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Section: Introductionmentioning

confidence: 69%

Developing Supply Chain Network With Piecewise Linear Transportation Cost for a Small-and-Medium Enterprise (Sme) in Cilegon

Kurniawan

Irman

Gunawan

et al. 2023

Majalah Ilmiah Pengkajian Industri

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show abstract

“…The value chain network design problem in the optimization model is a combinatorial planning problem with multiple constraints, and the metaheuristic algorithm has been proven to be an effective tool to solve the combinatorial planning problem with good performance in many scenarios [ 22 , 23 , 24 , 25 , 26 , 27 ]. Besides, in recent years, some scholars have combined genetic algorithms into other fields and achieved good results [ 28 , 29 , 30 , 31 ].…”

Section: Related Workmentioning

confidence: 99%

An Optimization Method of Production-Distribution in Multi-Value-Chain

Wang

Zhang

Ding

et al. 2023

Sensors

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Value chain collaboration management is an effective means for enterprises to reduce costs and increase efficiency to enhance competitiveness. Vertical and horizontal collaboration have received much attention, but the current collaboration model combining the two is weak in terms of task assignment and node collaboration constraints in the whole production-distribution process. Therefore, in the enterprise dynamic alliance, this paper models the MVC (multi- value-chain) collaboration process for the optimization needs of the MVC collaboration network in production-distribution and other aspects. Then a MVC collaboration network optimization model is constructed with the lowest total production-distribution cost as the optimization objective and with the delivery cycle and task quantity as the constraints. For the high-dimensional characteristics of the decision space in the multi-task, multi-production end, multi-distribution end, and multi-level inventory production-distribution scenario, a genetic algorithm is used to solve the MVC collaboration network optimization model and solve the problem of difficult collaboration of MVC collaboration network nodes by adjusting the constraints among genes. In view of the multi-level characteristics of the production-distribution scenario, two chromosome coding methods are proposed: staged coding and integrated coding. Moreover, an algorithm ERGA (enhanced roulette genetic algorithm) is proposed with enhanced elite retention based on a SGA (simple genetic algorithm). The comparative experiment results of SGA, SEGA (strengthen elitist genetic algorithm), ERGA, and the analysis of the population evolution process show that ERGA is superior to SGA and SEGA in terms of time cost and optimization results through the reasonable combination of coding methods and selection operators. Furthermore, ERGA has higher generality and can be adapted to solve MVC collaboration network optimization models in different production-distribution environments.

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“…Generate 1-5 true optimal incumbent facility locations, calculate 1-10 optimal locations of entrant facility by traditional branch and bound algorithm, and approximate branch and bound algorithm of Algorithm 2. Taking the results from the traditional branch (19)…”

Section: Performance Of Simultaneous Decisionmentioning

confidence: 99%

“…Yavari and Mousavi-Saleh [18] proposed the Extended Radius bi-levels restructuring capacitated facility location problem (ER-RCFLP), including opening, closing down and resizing new facilities, extended the location model as a hierarchical problem. In the two-stage capacitated facility location model, Mauri et al [19] proposed two hybrid metaheuristics for solving the multiproduct problem, the transportation cost and customer behavior were considered in computational experiments. Filippi et al [20] incorporated cost minimization and customer satisfaction as the objectives and constructed a fair single source capacitated facility location (F-SSCFL) problem, a weighted sum method was applied to generate a small set of solutions, and then, they implemented a Benders decomposition approach to handle large-scale instances.…”

Section: Introductionmentioning

confidence: 99%

Quantity decisions of two-stage competitive location model based on different location modes

2021

Complex Intell. Syst.

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The facility location of a competing firm in a market has great importance in supply chain management. The two-stage competitive location model formulates the decision process of an entrant firm facing both location and price competition. In this paper, we incorporated the facility quantity as a decision variable into a two-stage competitive location model with the objective of maximized profit. Sequential location mode and simultaneous location mode were applied to simulate different location behavior. We developed an approximate branch and bound method to accelerate optimal location searching speed under the premise of accuracy. Greedy algorithm and approximate branch and bound method were used in two location modes. From algorithm evaluation, we found that the approximate branch and bound method is an ideal supplement of the traditional branch and bound method, especially for location problems with large-scale potential locations. Compare the results of the two modes, we found when a new firm is going to enter a market with both price and location competition, sequential location mode is an advantage strategy, since it can gain more profit than simultaneous location mode.

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Hybrid metaheuristics to solve a multiproduct two‐stage capacitated facility location problem

Cited by 10 publications

References 36 publications

Developing Supply Chain Network With Piecewise Linear Transportation Cost for a Small-and-Medium Enterprise (Sme) in Cilegon

Developing Supply Chain Network With Piecewise Linear Transportation Cost for a Small-and-Medium Enterprise (Sme) in Cilegon

An Optimization Method of Production-Distribution in Multi-Value-Chain

Quantity decisions of two-stage competitive location model based on different location modes

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