A heuristic algorithm for solving flexible job shop scheduling problem

Ziaee, Mohsen

doi:10.1007/s00170-013-5510-z

Cited by 67 publications

(33 citation statements)

References 28 publications

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“…• The LEGA of Ho et al (2007), the BBO of Rahmati and Zandieh (2012), and the Heuristic of Ziaee (2014) are standard heuristic and metaheuristic methods.…”

Section: Experimental Comparisonsmentioning

confidence: 99%

“…This algorithm applied two steps, a first relaxation step, in which a sub-set of scheduling decisions was randomly retracted from the current solution, and a second solving step, in which a new solution was incrementally recomputed from this partial schedule. Moreover, a new heuristic was developed by Ziaee (2014) for the FJSP. This heuristic is based on a constructive procedure considering simultaneously many factors having a great effect on the solution quality.…”

Section: Introductionmentioning

confidence: 99%

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Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

2017

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The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NPhard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.

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“…• The LEGA of Ho et al (2007), the BBO of Rahmati and Zandieh (2012), and the Heuristic of Ziaee (2014) are standard heuristic and metaheuristic methods.…”

Section: Experimental Comparisonsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

2017

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“…Zribi et al [88] solved the FOSP by considering assignment and sequencing problems hierarchically. Two methods, based on local search and the branch and bound algorithm, were developed for the assignment problem while a hybridized EA was proposed for the sequencing.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective for a Partial Flexible Open Shop Scheduling Problem Using a Priority-Based Evolutionary Algorithm

Jananeeswari¹

2017

IJMPERD

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“…In recent years, scheduling plays a vital role in manufacturing environments due to the growing consumer demand for variety, reduced product life cycles, changing markets with global competition, and the rapid development of new technologies [1].…”

Section: Introductionmentioning

confidence: 99%

“…It has attracted the attention of many researchers [2][3][4] due to its wide applicability and inherent difficulty [1]. the flexible job shop scheduling problem (FJSP) is generally similar to the classical job-shop scheduling problem (JSP), but differs in the details of the machine assignment.…”

Section: Introductionmentioning

confidence: 99%

An Improved Ant Colony Optimization for Flexible Job Shop Scheduling Problem

Wang¹,

Cai²,

Zhi-hu³

et al. 2017

Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

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Abstract-This paper deals with the flexible job shop scheduling problem (FJSP) with the objective of minimizing the makespan. An improved ant colony optimization was proposed to avoid falling into the local optimum and time consuming exist in the basic ant colony optimization (ACO). Computational results show that the proposed improved ant colony optimization algorithm can obtain effective solutions in very short and nearly zero time and is comparable with some other heuristic algorithms and can effectively solve the FJSP.

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A heuristic algorithm for solving flexible job shop scheduling problem

Cited by 67 publications

References 28 publications

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

Multi-Objective for a Partial Flexible Open Shop Scheduling Problem Using a Priority-Based Evolutionary Algorithm

An Improved Ant Colony Optimization for Flexible Job Shop Scheduling Problem

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