Scheduling problem in a two-machine flow line with the<i>N</i>-step prior-job-dependent set-up times

Sun, Ji Ung; Hwang, Hark

doi:10.1080/002077201300029764

Cited by 13 publications

(4 citation statements)

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“…Hwang and Sun (1998) also considered the same problem, and presented a genetic algorithm to solve the problem. Sun and Hwang (2001) addressed a related problem of F2/ST sd /C max , where the setup times are present only on the second machine and the setup time of a job depends on k (k>1) immediately preceding jobs. They proposed a dynamic programming formulation and a genetic algorithm for the problem.…”

Section: Nonmentioning

confidence: 99%

A survey of scheduling problems with setup times or costs

Allahverdi

Cheng

et al. 2008

European Journal of Operational Research

1,115

467

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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 mid-1960s. 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 non-batching considerations, and with sequence-independent and sequence-dependent setup times. It further categorizes the literature according to shop environments, including single-machine, parallel machines, flow shop, no-wait flow shop, flexible flow shop, job shop, open shop, and others.

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Section: Nonmentioning

confidence: 99%

A survey of scheduling problems with setup times or costs

Allahverdi

Cheng

et al. 2008

European Journal of Operational Research

1,115

467

View full text Add to dashboard Cite

show abstract

“…They provide a dynamic programming formulation as an exact method and also develop a genetic algorithm with a problem-specific encoding. Sun and Hwang [26] further generalize this idea to "N-step prior job-dependent setup" times. They provide a practical example in which the length of the setup time required for a job depends not on the job immediately preceding it but rather on the job that appears in the schedule four positions earlier.…”

Section: Literature Reviewmentioning

confidence: 96%

Production scheduling with history‐dependent setup times

Lee

Lei

Pinedo

2012

Naval Research Logistics

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Abstract:We consider a parallel-machine scheduling problem with jobs that require setups. The duration of a setup does not depend only on the job just completed but on a number of preceding jobs. These setup times are referred to as history-dependent. Such a scheduling problem is often encountered in the food processing industry as well as in other process industries. In our model, we consider two types of setup times-a regular setup time and a major setup time that becomes necessary after several "hard-toclean" jobs have been processed on the same machine. We consider multiple objectives, including facility utilization, flexibility, number of major setups, and tardiness. We solve several special cases assuming predetermined job sequences and propose strongly polynomial time algorithms to determine the optimal timing of the major setups for given job sequences. We also extend our analysis to develop pseudopolynomial time algorithms for cases with additional objectives, including the total weighted completion time, the total weighted tardiness, and the weighted number of tardy jobs.

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“…Among all approaches, one of the most successful meta-heuristics to solve PFSP from last until now is genetic algorithm. Like one worked by Reeves (1995) and Sun and Hwang (2001). Sun and Hwang (2001) addressed a related problem of F 2 / ST sd /C max where the setup times are present only on the second machine, and the setup time of a job depends on k (k [ 1) immediately preceding jobs.…”

Section: Introductionmentioning

confidence: 99%

“…Like one worked by Reeves (1995) and Sun and Hwang (2001). Sun and Hwang (2001) addressed a related problem of F 2 / ST sd /C max where the setup times are present only on the second machine, and the setup time of a job depends on k (k [ 1) immediately preceding jobs. They proposed a dynamic programming formulation and a genetic algorithm for the problem.…”

Section: Introductionmentioning

confidence: 99%

A novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem

2014

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Flow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and setup costs of large permutation flow-shop scheduling problems with sequence-dependent setup times on each machine, this paper develops a novel hybrid genetic algorithm (HGA) with three genetic operators. Proposed HGA applies a modified approach to generate a pool of initial solutions, and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. We consider the make-to-order production approach that some sequences between jobs are assumed as tabu based on maximum allowable setup cost. In addition, the results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

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Scheduling problem in a two-machine flow line with theN-step prior-job-dependent set-up times

Cited by 13 publications

References 0 publications

A survey of scheduling problems with setup times or costs

A survey of scheduling problems with setup times or costs

Production scheduling with history‐dependent setup times

A novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem

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