An efficient implementation of a VNS/ILS heuristic for a real-life car sequencing problem

Ribeiro, Celso C.; Aloise, Daniel; Noronha, Thiago F.; Rocha, Caroline; Urrutia, Sebastián

doi:10.1016/j.ejor.2007.02.003

Cited by 27 publications

(17 citation statements)

References 5 publications

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“…In a future work, we intend to implement and incorporate into the ILS algorithm more sophisticated procedures and acceptance criteria, expecting to obtain better solutions than those presented in this study. For example, in an attempt to improve the local search, we may adopt a VNS approach, following the basic concepts of Ribeiro et al (2008) and Hansen and Mladenovic (2001). The generation of initial solutions, which is currently carried out almost purely at random, may also be modified by applying some greedy construction based on a previous evaluation of insertions of cut points.…”

Section: Computational Resultsmentioning

confidence: 99%

An iterative local search approach applied to the optimal stratification problem

Brito¹,

Ochi²,

Montenegro³

et al. 2010

Int Trans Operational Res

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Stratified sampling is a technique that consists in separating the elements of a population into nonoverlapping groups, called strata. This paper describes a new algorithm to solve the one-dimensional case, which reduces the stratification problem to just determining strata boundaries. Assuming that the number L of strata and the total sample size n are predetermined, we obtain the strata boundaries by taking into consideration an objective function associated with the variance. In order to solve this problem, we have implemented an algorithm based on the iterative local search metaheuristic. Computational results obtained from a real data set are presented and discussed.

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Section: Computational Resultsmentioning

confidence: 99%

An iterative local search approach applied to the optimal stratification problem

Brito¹,

Ochi²,

Montenegro³

et al. 2010

Int Trans Operational Res

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“…Ribeiro et al (2008a) propose a set of heuristics based on the paradigms of the VNS and ILS metaheuristics for a multi-objective real-life car sequencing problem with painting and assembly line constraints and Ribeiro et al (2008b) provide an efficient implementation of the VNS/ILS heuristic for this real-life car sequencing problem. Joly and Frein (2008) use VNS to tackle an industrial car sequencing problem considering paint and assembly shop objectives.…”

Section: Car Sequencingmentioning

confidence: 99%

Variable neighbourhood search: methods and applications

2009

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Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building heuristics, based upon systematic changes of neighbourhoods both in descent phase, to find a local minimum, and in perturbation phase to emerge from the corresponding valley. It was first proposed in 1997 and has since then rapidly developed both in its methods and its applications. In the present paper, these two aspects are thoroughly reviewed and an extensive bibliography is provided. Moreover, one section is devoted to newcomers. It consists of steps for developing a heuristic for any particular problem. Those steps are common to the implementation of other metaheuristics.

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“…They mentioned that sophisticated metaheuristics were impractical to solve the CSP. Ribeiro, et al [16], Ribeiro, et al [17] approximately solved the CSP using a set of heuristics based on the paradigms of the VNS and iterated local search (ILS) metaheuristics which were further enhanced with the intensification and diversification strategies. The optimised data structure for the effective implementation of heuristics was also proposed.…”

Section: Cspmentioning

confidence: 99%

Solving Many-Objective Car Sequencing Problems on Two-Sided Assembly Lines Using an Adaptive Differential Evolutionary Algorithm

Chutima¹,

Kirdphoksap²

2019

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The car sequencing problem (CSP) is addressed in this paper. The original environment of the CSP is modified to reflect real practices in the automotive industry by replacing the use of single-sided straight assembly lines with two-sided assembly lines. As a result, the problem becomes more complex caused by many additional constraints to be considered. Six objectives (i.e. many objectives) are optimised simultaneously including minimising the number of colour changes, minimising utility work, minimising total idle time, minimising the total number of ratio constraint violations and minimising total production rate variation. The algorithm namely adaptive multi-objective evolutionary algorithm based on decomposition hybridised with differential evolution algorithm (AMOEA/D-DE) is developed to tackle this problem. The performances in the Pareto sense of AMOEA/D-DE are compared with COIN-E, MODE, MODE/D and MOEA/D. The results indicate that AMOEA/D-DE outperforms the others in terms of convergencerelated metrics.

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An efficient implementation of a VNS/ILS heuristic for a real-life car sequencing problem

Cited by 27 publications

References 5 publications

An iterative local search approach applied to the optimal stratification problem

An iterative local search approach applied to the optimal stratification problem

Variable neighbourhood search: methods and applications

Solving Many-Objective Car Sequencing Problems on Two-Sided Assembly Lines Using an Adaptive Differential Evolutionary Algorithm

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