A memetic algorithm for the job-shop with time-lags

Caumond, Anthony; Lacomme, Philippe; Tchernev, Nikolay

doi:10.1016/j.cor.2006.11.007

Cited by 59 publications

(53 citation statements)

References 19 publications

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“…Caumond et al (2008) introduced a memetic algorithm, which is a combination of population based search and local search with an emphasis on using problem specific knowledge. Artigues et al (2011) proposed a CP branch and bound method using dichotomic search and the branching scheme of Torres and Lopez (2000).…”

Section: State-of-the-art Systematic and Metaheuristic Comparison Metmentioning

confidence: 99%

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Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Grimes

Hébrard

2015

INFORMS Journal on Computing

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We introduce a simple technique for disjunctive machine scheduling problems and show that this method can match or even outperform state of the art algorithms on a number of problem types. Our approach combines a number of generic search techniques such as restarts, adaptive heuristics and solution guided branching on a simple model based on a decomposition of disjunctive constraints and on the reification of these disjuncts. This paper describes the method and its application to variants of the job shop scheduling problem (JSP ).We show that our method can easily be adapted to handle additional side constraints and different objective functions, often outperforming the state of the art and closing a number of open problems.* Moreover, we perform in-depth analysis of the various factors that makes this approach efficient. We show that, while most of the factors give moderate benefits, the variable and value ordering components are key.

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Section: State-of-the-art Systematic and Metaheuristic Comparison Metmentioning

confidence: 99%

“…The TL-JSP instances that have been studied in the literature, as presented in Caumond et al (2008), were generated by adding time lag constraints to well known JSP benchmarks.…”

Section: Problem Typesmentioning

confidence: 99%

Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Grimes

Hébrard

2015

INFORMS Journal on Computing

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“…Our experiments were conducted on instances presented in [6,22]. These instances have been Table 5, one can observe the number of instances on which every heuristic is the best.…”

Section: Computational Resultsmentioning

confidence: 99%

“…A local search approach can be found in [19]. A memetic algorithm is proposed in [6] and obtained good results on jobshop instances, especially for those with null minimum and maximum time-lags (named as "no-wait problems").…”

Section: Discussionmentioning

confidence: 99%

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Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems

Huguet¹,

López²,

Karoui³

2012

J Math Model Algor

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In this paper, we propose mechanisms to improve instantiation heuristics by incorporating weighted factors on variables. The proposed weight-based heuristics are evaluated on several tree search methods such as chronological backtracking and discrepancy-based search for both constraint satisfaction and optimization problems. Experiments are carried out on random constraint satisfaction problems, car sequencing problems, and jobshop scheduling with time-lags, considering various parameter settings and variants of the methods. The results show that weighting mechanisms reduce the tree size and then speed up the solving time, especially for the discrepancy-based search method.

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Memetic Algorithms

Moscato

Berretta

Cotta

2011

Wiley Encyclopedia of Operations Research and Management Science

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Memetic algorithms (MAs) are population‐based search strategies that have been extensively used as metaheuristics for optimization problems in a large number of domains. They are based on the synergistic combination of different algorithmic solvers, with an emphasis on hybridizations with advanced mathematical programming techniques. The synergies are obtained by balancing competitive and cooperative interactions among software agents, which are allowed to have different search strategies and sporadically interact. The paradigm was specially designed for heterogeneous distributed systems and parallel computers 20 years ago. We present a brief historical perspective on MAs, an outline of their algorithmic structural template, and some relevant design aspects of these techniques. The strong momentum of the field is further illustrated by an overview of up‐to‐date algorithmic developments of the paradigm and by highlighting some of the most recent applications published in the literature.

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A memetic algorithm for the job-shop with time-lags

Cited by 59 publications

References 19 publications

Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search

Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems

Memetic Algorithms

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