Solving the bi‐objective capacitated <i>p</i>‐median problem with multilevel capacities using compromise programming and VNS

Irawan, Chandra Ade; Imran, Arif; Luis, Martino

doi:10.1111/itor.12485

Cited by 12 publications

(6 citation statements)

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“…The whole process is iterated until a predefined stopping condition (e.g., maximum number of iterations or maximum CPU time) is met. Many variants of VNS have been derived from the Basic VNS scheme and applied to different optimization problems (for a survey, see, e.g., Hansen et al, ; for recent publications, see Irawan et al, ; Janković et al, ; Pinto et al, ; Brimberg et al, ; Chagas et al, ; Gruler et al, ).…”

Section: Basic Variable Neighborhood Search For the Opmpmentioning

confidence: 99%

Less is more approach: basic variable neighborhood search for the obnoxious p‐median problem

Mladenović

Alkandari

Pei

et al. 2019

Int Trans Operational Res

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The goal of the less is more approach (LIMA) for solving optimization problems that has recently been proposed in Mladenović et al. (2016) is to find the minimum number of search ingredients that make a heuristic more efficient than the currently best. In this paper, LIMA is successfully applied to solve the obnoxious p‐median problem (OpMP). More precisely, we developed a basic variable neighborhood search for solving the OpMP, where the single search ingredient, the interchange neighborhood structure, is used. We also propose a new simple local search strategy for solving facility location problems, within the interchange neighborhood structure, which is in between the usual ones: first improvement and best improvement strategies. We call it facility best improvement local search. On the basis of experiments, it appeared to be more efficient and effective than both first and best improvement. According to the results obtained on the benchmark instances, our heuristic turns out to be highly competitive with the existing ones, establishing new state‐of‐the‐art results. For example, four new best‐known solutions and 133 ties are claimed in testing the set with 144 instances.

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Section: Basic Variable Neighborhood Search For the Opmpmentioning

confidence: 99%

Less is more approach: basic variable neighborhood search for the obnoxious p‐median problem

Mladenović

Alkandari

Pei

et al. 2019

Int Trans Operational Res

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“…Three methods were applied by El Amrani, Benadaa and Gendron (2016), namely a branch and cut algorithm, large neighbourhood search, and greatest customer demand first to address the CPMP considering the budget constraint into the problem. Irawan, Imran and Luis (2017) proposed the bi-objective CPMP with the fixed cost for opening the new facility and its capacities that can be utilized by potential facilities. The problem is solved by using a compromise programming approach.…”

Section: Literature Reviewmentioning

confidence: 99%

“…If the search process cannot find any improvement, the neighbourhood search applies the next neighbourhood (a larger one), otherwise, it reverts to the smaller neighbourhood. In this study, VNS-based matheuristic is constructed based on the one proposed by Irawan et al (2017). The VNS matheuristic main steps can be seen in Figure 2.…”

Section: The Vns Based Matheuristicmentioning

confidence: 99%

A simulation-based optimisation for the stochastic green capacitated p-median problem

Imran

Utomo

Ramadhan

et al. 2022

JIEM

Self Cite

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Purpose: This paper aims to propose a new model called the stochastic green capacitated p-median problem with a simulation-based optimisation approach. An integer linear programming mathematical model is built considering the total emission produced by vehicles and the uncertain parameters including the travel cost for a vehicle to travel from a particular facility to a customer and the amount of CO2 emissions produced. We also develop a simulation-based optimisation algorithm for solving the problem.Design/methodology/approach: The authors proposed new algorithms to solve the problem. The proposed algorithm is a hybridisation of Monte Carlo simulation and a Variable Neighbourhood Search matheuristic. The proposed model and method are evaluated using instances that are available in the literature.Findings: Based on the results produced by the computational experiments, the developed approach can obtain interesting results. The obtained results display that the proposed method can solve the problems within a short computational time and the solutions produced have good quality (small deviations).Originality/value: To the best of our knowledge, there is no paper in the previous literature investigating the simulation-based optimisation for the stochastic green capacitated p-median problem. There are two main contributions in this paper. First, to build a new model for the capacitated p-median problem taking into account the environmental impact. Second, to design a simulation-based optimisation approach to solve the stochastic green capacitated p-median problem incorporating VNS-based matheuristic and Monte Carlo simulation.

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“…The actual calculation results show that this integrated model is more efficient than existing models. Another trial research, such as literature [25,26], also investigated the integrated model for the bi-objective capacitated P-median problem with multilevel capacities. Their research contributed to a good way to make use of advantages from these two kinds of models, but did not meet exactly four requirements of the URT maintenance network we study.…”

Section: Multi-facility Location-allocation Model In the Networkmentioning

confidence: 99%

Maintenance Decision-Making of an Urban Rail Transit System in a Regionalized Network-Wide Perspective

et al. 2020

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The networked operation of Urban Rail Transit (URT) brings the new challenge of network-wide maintenance. This research focuses on the URT Network-Wide Maintenance Decision-Making Problem (URT-NMDP), including regionalized maintenance network design and maintenance resource allocation. In this work, we proposed a bi-objective integer programming model that integrates the characteristics of set coverage and P-median models, resulting in the regionalized maintenance network design model. Some critical factors are considered in the model, such as the importance of node, the maximum failure response time, and maintenance guarantee rules. We designed a NSGA-II based algorithm to solve the model. Moreover, due to the uncertainty of failures in the URT network, we developed the method of allocating maintenance resources based on Monte Carlo simulation to strengthen the reliability of the regionalized maintenance network. With the model and algorithm presented in this work, we obtained Pareto optimal solutions of URT-NMDP, i.e., URT network-wide maintenance planning schemes, which include the number and location of maintenance points, the allocation of demand points, and the amount of maintenance units. Finally, a real-world case is studied to evaluate the operating performance of these schemes for verifying the method in our paper. The results of the case study demonstrate that the reasonable and tested-in-practice maximum failure response time is the precondition for the efficient URT maintenance network. The maintenance scheme considered the weighted importance of node shows the optimal performance, with the shortest overall maintenance path and the minimum average failure response time and investment cost on maintenance resources.

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Solving the bi‐objective capacitated p‐median problem with multilevel capacities using compromise programming and VNS

Cited by 12 publications

References 50 publications

Less is more approach: basic variable neighborhood search for the obnoxious p‐median problem

Less is more approach: basic variable neighborhood search for the obnoxious p‐median problem

A simulation-based optimisation for the stochastic green capacitated p-median problem

Maintenance Decision-Making of an Urban Rail Transit System in a Regionalized Network-Wide Perspective

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