No-wait and blocking job-shops: challenging problems for GA's

Brizuela, Carlos A.; Zhao, Yong; Sannomiya, Nobuo

doi:10.1109/icsmc.2001.972908

Cited by 16 publications

(13 citation statements)

References 12 publications

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“…Order Crossover (ODX) is used in the HGA since Brizuela et al (2001) reported good results for GA with ODX in NWJS problems. The procedures of ODX are as follows (Cheng, Gen, & Tsujimura, 1999):…”

Section: Crossover and Mutationmentioning

confidence: 99%

“…(7) Jobs are not allowed to reenter previous machines. Brizuela et al (2001) proposed an integer programming model for NWJS based on the classical job shop model of Baker (1974). In their model, a set of constraints is modified to meet the no-wait requirement.…”

Section: Problem Assumptionsmentioning

confidence: 99%

“…Macchiaroli, Molè, Riemma, and Trifiletti (1996) presented a two-phase tabu search (TS) approach and found that it generated better solutions than those of the dispatching rules by an average of 9%. Brizuela, Zhao, and Sannomiya (2001) proposed a genetic algorithm (GA) using simple encoding and adequate decoding techniques to solve classical job shop benchmark problems with no-wait constraints.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A hybrid genetic algorithm for no-wait job shop scheduling problems

Pan¹,

Huang²

2009

Expert Systems with Applications

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Section: Crossover and Mutationmentioning

confidence: 99%

Section: Problem Assumptionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A hybrid genetic algorithm for no-wait job shop scheduling problems

Pan¹,

Huang²

2009

Expert Systems with Applications

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“…[4] and [5] formulate these problems by means of alternative graphs. [7] develop a genetic algorithm for solving no-wait and Blocking Job Shop problems and [8] and [9] introduce a local search approach for the generalized Blocking Job Shop problem with application in automated warehouses. [6] study a multi-resource job shop problem with blocking constraints.…”

Section: Introductionmentioning

confidence: 99%

Mixed Integer Linear Programs for Blocking and No Wait Job Shop Scheduling Problems in Robotic cells

Louaqad¹,

Kamach²

2016

IJCA

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This paper studies the problem of scheduling Job shops in robotic cells with no intermediate buffers, called No Wait Blocking Transport Job Shop Scheduling Problem (NWBT JSSP). This problem is an extension of the classical job shop problem. No Wait Blocking Transport job shop problems arise in many realistic production environments. To tackle this problem, we developed a Mixed Integer Linear Program and proposed a constructive heuristic based on priority rules. The MILP model has been used to solve optimally problems with as many as ten jobs, ten machines and three robots. Computational results on hypothetically generated test problems are discussed and suggestions of future research projects are proposed.

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“…The no-wait and blocking JSSP consists of a JSSP where at least two operations are constrained such that the second operation has to start immediately upon completion of the first operation (Brizuela et al 2001;Mascis and Pacciarelli 2002;Meloni et al 2004;and Schuster and Framinan 2003). The reentrant JSSP allows the processing of two operations from the same job on the same machine (Aldakhilallah andRamesh 2001 and while the cyclic job shop consists of operations which are repeated in a cyclic fashion (Brucker and Kampmeyer 2005;Cavory et al 2005;and Nakamura et al 2000).…”

Section: The Problem Contextmentioning

confidence: 99%

Metaheuristics for the multi-objective FJSP with sequence-dependent set-up times, auxiliary resources and machine down time

Grobler

Engelbrecht²,

Kok³

et al. 2009

Ann Oper Res

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This paper investigates the application of particle swarm optimization (PSO) to the multi-objective flexible job shop scheduling problem with sequence-dependent set-up times, auxiliary resources and machine down time. To achieve this goal, alternative particle representations and problem mapping mechanisms were implemented within the PSO paradigm. This resulted in the development of four PSO-based heuristics. Benchmarking on real customer data indicated that using the priority-based representation resulted in a significant performance improvement over the existing rule-based algorithms commonly used to solve this problem. Additional investigation into algorithm scalability led to the development of a priority-based differential evolution algorithm. Apart from the academic significance of the paper, the benefit of an improved production schedule can be generalized to include cost reduction, customer satisfaction, improved profitability, and overall competitive advantage.

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No-wait and blocking job-shops: challenging problems for GA's

Cited by 16 publications

References 12 publications

A hybrid genetic algorithm for no-wait job shop scheduling problems

A hybrid genetic algorithm for no-wait job shop scheduling problems

Mixed Integer Linear Programs for Blocking and No Wait Job Shop Scheduling Problems in Robotic cells

Metaheuristics for the multi-objective FJSP with sequence-dependent set-up times, auxiliary resources and machine down time

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