Scheduling identical parallel batch processing machines to minimise makespan using genetic algorithms

Damodaran, Purushothaman; Hirani, Neal S.; Vélez-Gallego, Mario C.

doi:10.1504/ejie.2009.023605

Cited by 51 publications

(17 citation statements)

References 27 publications

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“…Another interesting topic regarding parallel machine scheduling problems is to consider multiobjective optimisation. Other parallel machines problems like for example with batching machines (Damodaran et al, 2009) seems also interesting.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times

Vallada

Ruíz

2011

European Journal of Operational Research

323

254

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In this work a genetic algorithm is presented for the unrelated parallel machine scheduling problem in which machine and job sequence dependent setup times are considered. The proposed genetic algorithm includes a fast local search and a local search enhanced crossover operator. Two versions of the algorithm are obtained after extensive calibrations using the Design of Experiments (DOE) approach. We review, evaluate and compare the proposed algorithm against the best methods known from the literature. We also develop a benchmark of small and large instances to carry out the computational experiments. After an exhaustive computational and statistical analysis we can conclude that the proposed method shows an excellent performance overcoming the rest of the evaluated methods in a comprehensive benchmark set of instances.

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Section: Conclusion and Future Researchmentioning

confidence: 99%

A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times

Vallada

Ruíz

2011

European Journal of Operational Research

323

254

View full text Add to dashboard Cite

show abstract

“…These problems may be compared to the problems studied here, applying the heuristics presented in this paper to solve them, or even developing more sophisticated methods based on these heuristics. Finally, the addressed scheduling problem may be applied to other scheduling environments such as single or parallel machine environments, e.g., Damodaran et al (2009), Chen et al (2009. Also, in order to minimize the total cost of inventory (e.g., see Singh and Chand, 2009, Warburton, 2009, Sharma, 2009) other objective functions that take into account factors to minimize the cost of inventory may be investigated.…”

Section: Discussionmentioning

confidence: 99%

Setting a common due date in a constrained flowshop: A variable neighbourhood search approach

González

2010

Computers & Operations Research

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In this paper we study a due date setting problem in a flowshop layout. The problem consists of scheduling a set of jobs arriving to the system together with jobs already present (denoted as old jobs), in order to set a common due date for the new jobs. Since the old jobs have a common due date that must not be violated, our problem is a rescheduling problem with the objective of minimising the makespan of the new jobs (thus obtaining the tightest possible due date for the new jobs) and a constraint since the maximum tardiness of the old jobs must be equal to zero.This approach leads to an interesting scheduling problem in which two different objectives are considered, each one for a subset of the jobs that must be scheduled.To the best of our knowledge, this type of problems have been scarcely considered in the literature, and only for very specific purposes. Since our problem is clearly NP-hard, a new heuristic based on Variable Neighbourhood Search (VNS) has been designed. The computational results show that our proposed heuristic outperforms two existing heuristic methods for similar problems in the literature. * This is an Accepted Manuscript of an article published by Elsevier in

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“…Chang et al, 2007;Luo et al, 2009;Damodaran et al, 2009;Ventura and Yoon, 2013;Li et al, 2014;Chang and Liu, 2015 This scheme of GA has been implemented using both codi cations presented in the previous section: permutation and binary codi cation denoted GA(P) and GA(B) respectively . Both algorithms are identical, except with respect to the tness computation, since the way to calculate the owtime is simpler in the binary codi cation than in the permutation codi cation.…”

Section: Genetic Algorithmmentioning

confidence: 99%

Single machine interfering jobs problem with flowtime objective

González

2015

J Intell Manuf

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)>IJH=?J Interfering jobs problems (or multi agents scheduling problems) are an emergent topic in the scheduling literature. In these decision problems, two or more sets of jobs have to be scheduled, each one with its own criteria. More speci cally, we focus on a problem in which jobs belonging to two sets have to be scheduled in a single machine in order to minimize the total owtime of the jobs in one set, while the total owtime of the jobs in the other set should not exceed a given constant ϵ. This problem is known to be weakly NP-hard, and a Dynamic Programming (DP) algorithm has been proposed to nd optimal solutions.In this paper, we rst analyse the distribution of solutions of the problem in order to establish its empirical hardness. Next, a novel encoding scheme and a set of properties associated to the neighbourhood of this scheme are presented. These properties are used to develop both exact and approximate methods, i.e. a branch and bound (B&B) method, several constructive heuristics, and di erent versions of a genetic algorithm (GA). The computational experience carried out shows that the proposed B&B is more e cient than the existing DP algorithm. The results also show the advantages of the proposed encoding scheme, as the approximate methods yield close-to-optimum solutions for big-sized instances where exact methods are not feasible.Scheduling interfering jobs two-agent scheduling problem total owtime single machine

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Scheduling identical parallel batch processing machines to minimise makespan using genetic algorithms

Cited by 51 publications

References 27 publications

A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times

A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times

Setting a common due date in a constrained flowshop: A variable neighbourhood search approach

Single machine interfering jobs problem with flowtime objective

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