Sequencing of jobs in some production system

Grabowski, J.; Pempera, Jarosław

doi:10.1016/s0377-2217(99)00224-6

Cited by 198 publications

(69 citation statements)

References 11 publications

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“…[36] presented a TS heuristic for a two stage flexible flow line with makespan criterion. Another TS was proposed by [55] in a no-wait HFS inspired by a real manufacturing problem. In [216], the capacity between stages is limited (block).…”

Section: Metaheuristicsmentioning

confidence: 99%

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The hybrid flow shop scheduling problem

Ruíz

Vázquez-Rodríguez

2010

European Journal of Operational Research

646

236

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The scheduling of flow shops with multiple parallel machines per stage, usually referred to as the Hybrid Flow Shop (HFS), is a complex combinatorial problem encountered in many real world applications. Given its importance and complexity, the HFS problem has been intensively studied. This paper presents a literature review on exact, heuristic and metaheuristic methods that have been proposed for its solution.The paper discusses several variants of the HFS problem, each in turn considering different assumptions, constraints and objective functions. Research opportunities in HFS are also discussed.

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Section: Metaheuristicsmentioning

confidence: 99%

“…HFS is found in all kinds of real world scenarios including the electronics [217], [218], [118], [87], paper, [177] and textile, [55], industries. Examples are also found in the production of concrete, [143], the manufacturing of photographic film, [197,4], and others, [2,42,3,116,20,224,159].…”

Section: Introductionmentioning

confidence: 99%

The hybrid flow shop scheduling problem

Ruíz

Vázquez-Rodríguez

2010

European Journal of Operational Research

646

236

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“…Next, two particles x 1,3 and x 1,5 have equal position value i.e., 4.37. Yet, index of x 1,3 is smaller as compared to x 1,5 . So, X1,3 is assigned the next rank value of 2 and x 1,5 is incremented to rank value 3.…”

Section: Solution Representationmentioning

confidence: 89%

Evolutionary Hybrid Particle Swarm Optimization Algorithm for Solving NP-Hard No-Wait Flow Shop Scheduling Problems

Bewoor

Prakash

Sapkal³

2017

Algorithms

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Abstract:The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for improving the utilization of resources may become trapped in local optima, and this problem can hence be observed as a typical NP-hard combinatorial optimization problem that requires finding a near optimal solution with heuristic and metaheuristic techniques. This paper proposes an effective hybrid Particle Swarm Optimization (PSO) metaheuristic algorithm for solving no-wait flow shop scheduling problems with the objective of minimizing the total flow time of jobs. This Proposed Hybrid Particle Swarm Optimization (PHPSO) algorithm presents a solution by the random key representation rule for converting the continuous position information values of particles to a discrete job permutation. The proposed algorithm initializes population efficiently with the Nawaz-Enscore-Ham (NEH) heuristic technique and uses an evolutionary search guided by the mechanism of PSO, as well as simulated annealing based on a local neighborhood search to avoid getting stuck in local optima and to provide the appropriate balance of global exploration and local exploitation. Extensive computational experiments are carried out based on Taillard's benchmark suite. Computational results and comparisons with existing metaheuristics show that the PHPSO algorithm outperforms the existing methods in terms of quality search and robustness for the problem considered. The improvement in solution quality is confirmed by statistical tests of significance.

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“…This problem varies from its classic equivalent (through a classic equivalent, the job-shop problem with no constraints is understood) where the requirement of the beginning time of an operation should be exactly as that time when the technological predecessor finishes its operation execution. This constraint is very often met not only in those branches of industry where the transformed product changes quickly its physical-chemical properties, e.g., in drug production (Raaymakers and Hoogeveen [9]), foodstuff production (Hall and Sriskandarajah [6]), steel melting (Wismer [16]), or concrete elements manufacturing (Grabowski and Pempera [5]), but also in other branches like in semiconductors testing (Ovacik and Uzsoy [14]) or in computer systems (Reddi and Ramamoorth [10]). …”

Section: Description Of the Problemmentioning

confidence: 99%