Giffler and Thompson Procedure Based Genetic Algorithms for Scheduling Job Shops

Ponnambalam, S. G.; Jawahar, N.; Girish, B S

doi:10.1007/978-3-642-02836-6_8

Cited by 7 publications

(5 citation statements)

References 35 publications

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“…Girish and Jawahar [15] proposed a GA for the FJSP for minimum makespan time criterion. Ponnambalam et al [16] employed a genetic algorithm (GA)-based heuristics that have adopted the Giffler and Thompson (GT) procedure, an efficient and active feasible schedule for makespan time criterion. Giovanni and Pezzella [17] proposed an improved GA to solve the distributed FJSP to minimize the makespan.…”

Section: Related Workmentioning

confidence: 99%

A new genetic algorithm for flexible job-shop scheduling problems

2015

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Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.

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Section: Related Workmentioning

confidence: 99%

A new genetic algorithm for flexible job-shop scheduling problems

2015

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“…Since the problem is NP-hard, the state-of-the-art solution methodologies mainly include heuristic and metaheuristic approaches. Giffler and Thompson (GT) algorithm is a well-known procedure to construct active schedules for a given priority order of operations in JSP with makespan, tardiness and flowtime-based objectives [17,26]. The schedule generation mechanism in the GT algorithm also allows it to be used with dynamic priority dispatching rules, in which the job priorities change continuously over time during schedule generation [1,8,17].…”

Section: Introductionmentioning

confidence: 99%

Minimizing the total weighted earliness and tardiness for a sequence of operations in job shops

Girish

Habibullah

J³

2022

RAIRO-Oper. Res.

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This paper proposes exact algorithms to generate optimal timing schedules for a given sequence of operations in job shops to minimize the total weighted earliness and tardiness. The algorithms are proposed for two job shop scheduling scenarios, one involving due dates only for the last operation of each job and the other involving due dates for all operations on all the jobs. Computational experiments on benchmark problem instances reveal that, in the case of the scheduling scenario involving due dates only for the last operation of each job, the proposed exact algorithms generate schedules faster than those generated using a popular optimization solver. In the case of the scheduling scenario involving due dates for all operations on all the jobs, the exact algorithms are competitive with the optimization solver in terms of computation time for small and medium size problems.

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“…ACO algorithms can also effectively solve the scheduling problems with employee allocation [16] and multiple objectives [17,18]. An ant colony optimization approach (ACO) is also widely used for the shop scheduling [19][20][21][22][23] resource-constrained scheduling (RCS) and resource-constrained project scheduling problems (RCPSP) [24]. Novel operation scheduling algorithms using the ant colony optimization approach for both timing-constrained scheduling (TCS) and RCS is proposed in [25].…”

Section: Introductionmentioning

confidence: 99%

Ant colony optimisation for scheduling of flexible job shop with multi-resources requirements

et al. 2017

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Abstract. The paper presents application of ant colony optimisation algorithm for scheduling multi-resources operations in flexible job shop type of production systems. Operations that require the participation of two or more resources are common in industrial practice, when planning are subject not only machines, but also other additional resources (personnel, tools, etc.). Resource requirements of operation are indicated indirectly by resource groups. The most important parameters of the resource model and resource groups are also described. A basic assumptions for ant colony algorithm used for scheduling in the considered model with multiresources requirements of operations is discussed. The main result of the research is the schema of metaheuristic that enables searching best-score solutions in manufacturing systems satisfying presented constraints.

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Giffler and Thompson Procedure Based Genetic Algorithms for Scheduling Job Shops

Cited by 7 publications

References 35 publications

A new genetic algorithm for flexible job-shop scheduling problems

A new genetic algorithm for flexible job-shop scheduling problems

Minimizing the total weighted earliness and tardiness for a sequence of operations in job shops

Ant colony optimisation for scheduling of flexible job shop with multi-resources requirements

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