Flexible job-shop scheduling with parallel variable neighborhood search algorithm

Yazdani, Mehdi; Amiri, Maghsoud; Zandieh, M.

doi:10.1016/j.eswa.2009.06.007

Cited by 209 publications

(68 citation statements)

References 19 publications

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“…We compare AFSA-ED with the PVNS of Yazdani et al 41 , the CDDS of Ben Hmida et al 37 , the BEDA of Wang et al 42 , the ABC and the HHS. represents the best known solution ever reported in the literature for each instance.…”

Section: Results Of Brdata Problemsmentioning

confidence: 99%

An Efficient Artificial Fish Swarm Model with Estimation of Distribution for Flexible Job Shop Scheduling

Ge¹,

Sun²,

Chen³

et al. 2016

IJCIS

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The flexible job shop scheduling problem (FJSP) is one of the most important problems in the field of production scheduling, which is the abstract of some practical production processes. It is a complex combinatorial optimization problem due to the consideration of both machine assignment and operation sequence. In this paper, an efficient artificial fish swarm model with estimation of distribution (AFSA-ED) is proposed for the FJSP with the objective of minimizing the makespan. Firstly, a pre-principle and a post-principle arranging mechanism that operate by adjusting machine assignment and operation sequence with different orders are designed to enhance the diversity of population. Following this, the population is divided into two sub-populations and then two arranging mechanisms are applied. In AFSA-ED, a preying behavior based on estimation of distribution is proposed to improve the performance of algorithm. Moreover, an attracting behavior is proposed to improve the global exploration ability and a public factor based critical path search strategy is proposed to enhance the local exploitation ability. Simulated experiments are carried on BRdata, BCdata and HUdata benchmark sets. The computational results validate the performance of the proposed algorithm in solving the FJSP, as compared with some other state of the art algorithms.

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Section: Results Of Brdata Problemsmentioning

confidence: 99%

An Efficient Artificial Fish Swarm Model with Estimation of Distribution for Flexible Job Shop Scheduling

Ge¹,

Sun²,

Chen³

et al. 2016

IJCIS

View full text Add to dashboard Cite

show abstract

“…On the other hand, Mastrolilli and Gambardella [55], Gao et al [28], Pezzella et al [66], Amiri et al [3], Yazdani et al [81], Yuan and Xu [83] and Driss et al [20] have better result for the makespan than pbEA.…”

Section: Kacem Data Setmentioning

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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“…He and Zeng [8] set makespan as an objective, designing a Bayesian statistical inference-based estimation of distribution algorithm and adopting some benchmarks to prove the algorithm. Yazdani et al [9] proposed a parallel variable neighbourhood search (PVNS) to solve FJSP in an effort to minimize makespan.…”

Section: Flexible Job-shop Scheduling Problem (Fjsp)mentioning

confidence: 99%

Modelling and Simulation of a Multi-Resource Flexible Job-Shop Scheduling

Ba¹,

Li²,

Yang³

2016

Int. j. simul. model.

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Flexible job-shop scheduling problem (FJSP) in the field of production scheduling presents a quite difficult combinatorial optimization problem. Machines are mostly considered to be the only resource in many research projects dealing with FJSP. In actual production, there are many other factors which influence production scheduling, such as transportation, storage and detection. If machines are considered to be the only resource, the problem may not be in accord with the actual production. Thus, in order to make FJSP more in line with the real production situation, machines, warehouses, vehicles and detection equipment are all considered to be the scheduled resources simultaneously due to the shortage of flexible job shop scheduling problem in resources. A new mathematical model for a multiresource flexible job-shop scheduling problem (MRFJSP) is proposed. The constraints of the model are presented. The makespan is the main target which will be minimized. A genetic algorithm which includes elitist strategy is proposed to solve the MRFJSP. Due to the complexity of MRFJSP, each key module of the genetic algorithm is redesigned. Finally, the model and algorithm are proved through an application case.

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Flexible job-shop scheduling with parallel variable neighborhood search algorithm

Cited by 209 publications

References 19 publications

An Efficient Artificial Fish Swarm Model with Estimation of Distribution for Flexible Job Shop Scheduling

An Efficient Artificial Fish Swarm Model with Estimation of Distribution for Flexible Job Shop Scheduling

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

Modelling and Simulation of a Multi-Resource Flexible Job-Shop Scheduling

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