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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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Cited by 104 (5 self)
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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.
A Discrete Differential Evolution Algorithm for the Permutation Flowshop Scheduling Problem
"... In this paper, a novel discrete differential evolution (DDE) algorithm is presented to solve the permutation flowhop scheduling problem with the makespan criterion. The DDE algorithm is simple in nature such that it first mutates a target population to produce the mutant population. Then the target ..."
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Cited by 18 (1 self)
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In this paper, a novel discrete differential evolution (DDE) algorithm is presented to solve the permutation flowhop scheduling problem with the makespan criterion. The DDE algorithm is simple in nature such that it first mutates a target population to produce the mutant population. Then the target population is recombined with the mutant population in order to generate a trial population. Finally, a selection operator is applied to both target and trial populations to determine who will survive for the next generation based on fitness evaluations. As a mutation operator in the discrete differential evolution algorithm, a destruction and construction procedure is employed to generate the mutant population. We propose a referenced local search, which is embedded in the discrete differential evolution algorithm to further improve the solution quality. Computational results show that the proposed DDE algorithm with the referenced local search is very competitive to the iterated greedy algorithm which is one of the best performing algorithms for the permutation flowshop scheduling problem in the literature.
Better Heuristics for a TwoStage MultiMachine Assembly Scheduling Problem to Minimize Total Completion Time
, 2012
"... Abstract ⎯ We address the twostage multimachine assembly scheduling problem to minimize total completion times of all jobs. The first stage consists of m independently working machines where each machine produces its own component. The second stage consists of two independent and identical assembl ..."
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Abstract ⎯ We address the twostage multimachine assembly scheduling problem to minimize total completion times of all jobs. The first stage consists of m independently working machines where each machine produces its own component. The second stage consists of two independent and identical assembly machines. The processing of a job at the second stage cannot start until its m components, produced by the m machines at the first stage, are complete. This problem has been recently addressed in the literature for which an efficient heuristic, called SAK, was developed for the case when m=2. In this paper, we address the problem for the case m≥2. We propose a hybrid tabu search (HTS) heuristic and show that the overall average error of SAK is more than twice that of HTS while the average CPU time of SAK is five times that of HTS. This clearly indicates that the heuristic HTS is much better than the only existing heuristic available for the problem, i.e., SAK. We also propose two more heuristics, called SDE and NSDE, and show that the overall average error of SDE is about half of that of HTS. Furthermore, we show that the overall average error of NSDE is about one third that of SDE.
Available online at www.sciencedirect.com
, 2009
"... Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems ..."
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Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems
A Multiobjective State Transition Algorithm for Single Machine Scheduling
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