Multi-objective flexible job shop schedule: Design and evaluation by simulation modeling

Xing, Lining; Chen, Yingwu; Yang, Kewei

doi:10.1016/j.asoc.2008.04.013

Cited by 97 publications

(38 citation statements)

References 36 publications

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“…Therefore, a GA can be easily applied and modified for a variety of production optimization criteria in a job-shop environment that includes sequence-dependent setup times. Xing 104 presented a simulation model to solve the multiobjective flexible job-shop scheduling problem which was coded by Matlab and a special mathematical computation language. After modeling the pending problem, the model is validated by five representative instances based on practical data.…”

Section: Background On Multi-criteria Scheduling (Job-shop)mentioning

confidence: 99%

Review on Job-Shop and Flow-Shop Scheduling Using

Parveen

Ullah

2011

J. mech. eng.

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Section: Background On Multi-criteria Scheduling (Job-shop)mentioning

confidence: 99%

Review on Job-Shop and Flow-Shop Scheduling Using

Parveen

Ullah

2011

J. mech. eng.

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“…Otherwise, a small weight for the given objective can be defined. In this work the weight coefficients W 1 , W 2 , and W 3 for the five Kacem instances are set to 0.5, 0.3 and 0.2 according to Xing et al (2009aXing et al ( , 2009b. The advantage of utilizing the weighted summation approach is its algorithmic actualization which is effortless and the users can change the weight of different objectives for satisfying the requirements of decision makers.…”

Section: Problem Formulationmentioning

confidence: 99%

A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems

Karthikeyan

Asokan

Nickolas

et al. 2015

IJBIC

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Firefly Algorithm (FA) is a nature-inspired optimization algorithm that can be successfully applied to continuous optimization problems. However, lot of practical problems are formulated as discrete optimization problems. In this paper a hybrid discrete firefly algorithm (HDFA) is proposed to solve the multi-objective flexible job shop scheduling problem (FJSP). FJSP is an extension of the classical job shop scheduling problem that allows an operation to be processed by any machine from a given set along different routes. Three minimization objectives -the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. This paper also proposes firefly algorithm's discretization which consists of constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In the proposed algorithm discrete firefly algorithm (DFA) is combined with local search (LS) method to enhance the searching accuracy and information sharing among fireflies. The experimental results on the well-known benchmark instances and comparison with other recently published algorithms shows that the proposed algorithm is feasible and an effective approach for the multi-objective flexible job shop scheduling problems.

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“…The proposed method is used for solving the multi-objective Flexible Job Shop Scheduling Problems (FJSP). Other approaches to multi-objective decison making are shown in [7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective decision making and search space for the evaluation of production process scheduling

Witkowski¹,

Antczak²,

Antczak³

2009

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. Over the years, various approaches have been proposed in order to solve the multi-objective job-shop scheduling problemparticularly a hard combinatorial optimization problem. The paper presents an evaluation of job shop scheduling problem under multiple objectives (mean flow time, max lateness, mean tardiness, mean weighted tardiness, mean earliness, mean weighted earliness, number of tardy tasks). The formulation of the scheduling problem has been presented as well as the evaluation schedules for various optimality criteria. The paper describes the basic mataheuristics used for optimization schedules and the approaches that use domination method, fuzzy method, and analytic hierarchy proccess (AHP) for comparing schedules in accordance with multiple objectives. The effectiveness of the algorithms has been tested on several examples and the results have been shown. New search space for evaluation and generation of schedules has been created. The three-dimensional space can be used for the analysis and control of the production processes.

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Multi-objective flexible job shop schedule: Design and evaluation by simulation modeling

Cited by 97 publications

References 36 publications

Review on Job-Shop and Flow-Shop Scheduling Using

Review on Job-Shop and Flow-Shop Scheduling Using

A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems

Multi-objective decision making and search space for the evaluation of production process scheduling

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