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A Survey of Scheduling Problems with Setup Times or Costs
"... The first comprehensive survey paper on scheduling problems with separate setup times or costs was conducted by Allahverdi et al. (1999), who reviewed the literature since the mid1960s. Since the appearance of that survey paper, there has been an increasing interest in scheduling problems with setu ..."
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The first comprehensive survey paper on scheduling problems with separate setup times or costs was conducted by Allahverdi et al. (1999), who reviewed the literature since the mid1960s. Since the appearance of that survey paper, there has been an increasing interest in scheduling problems with setup times (costs) with an average of more than 40 papers per year being added to the literature. The objective of this paper is to provide an extensive review of the scheduling literature on models with setup times (costs) from then to date covering more than 300 papers. Given that so many papers have appeared in a short time, there are cases where different researchers addressed the same problem independently, and sometimes by using even the same technique, e.g., genetic algorithm. Throughout the paper we identify such areas where independently developed techniques need to be compared. The paper classifies scheduling problems into those with batching and nonbatching considerations, and with sequenceindependent and sequencedependent setup times. It further categorizes the literature according to shop environments, including singlemachine, parallel machines, flow shop, nowait flow shop, flexible flow shop, job shop, open shop, and others.
New Heuristics for NoWait Flowshops with Bicriteria of Makespan and Maximum Lateness
"... In this work we study a flowshop scheduling problem in which jobs are not allowed to wait inbetween machines, a situation commonly referred to as nowait. The concerned criterion is to minimize a weighted sum of makespan and maximum lateness. A dominance relation for the case of threemachine is pr ..."
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In this work we study a flowshop scheduling problem in which jobs are not allowed to wait inbetween machines, a situation commonly referred to as nowait. The concerned criterion is to minimize a weighted sum of makespan and maximum lateness. A dominance relation for the case of threemachine is presented and evaluated by experimental designs. Several heuristics and local search methods are proposed for the general mmachine case. The local search methods are based on genetic algorithms and iterated greedy procedures. An extensive computational analysis is conducted where it is shown that the proposed methods outperform existing heuristics and metaheuristics in all tested scenarios by a considerable margin and under identical CPU times. Keywords: Nowait flowshop, bicriteria, makespan, maximum lateness, dominance relation
A Particle Swarm Optimization Approach for the EarlinessTardiness NoWait Flowshop Scheduling Problem
"... Abstract—In this researcha particle swarm optimization (PSO) algorithm is proposedfor nowait flowshopsequence dependent setuptime scheduling problem with weighted earlinesstardiness penalties as the criterion (  ,  ∑).The smallestposition value (SPV) rule is applied to convert the continuous v ..."
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Abstract—In this researcha particle swarm optimization (PSO) algorithm is proposedfor nowait flowshopsequence dependent setuptime scheduling problem with weighted earlinesstardiness penalties as the criterion (  ,  ∑).The smallestposition value (SPV) rule is applied to convert the continuous value of position vector of particles in PSO to job permutations.A timing algorithm is generated to find the optimal schedule and calculate the objective function value of a given sequence in PSO algorithm. Twodifferent neighborhood structures are applied to improve the solution quality of PSO algorithm.The first one is based on variable neighborhood search (VNS) and the second one is a simple one with invariable structure. In order to compare the performance of two neighborhood structures, random test problems are generated and solved by both neighborhood approaches.Computational results show that the VNS algorithmhas better performance than the other one especially for the large sized problems. Keywords—minimization of summation of weighed earliness and tardiness, nowaitflowshop scheduling, particle swarm optimization, sequence dependent setup times I I.