Job Shop Scheduling with Dynamic Fuzzy Selection of Dispatching Rules

Subramaniam, Velusamy; Ramesh, T.; Lee, G. K.; Wong, Yoke San; Gao, Hong

doi:10.1007/s001700070029

Cited by 56 publications

(18 citation statements)

References 26 publications

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“…A fuzzy scheduler yields superior average flowtime, average tardiness, and average lateness performance over other simple routing heuristics such as WINQ and SPT. Other references of interest include (Murata et al, 1998;Sakawa and Kubota, 2000;Subramaniam et al, 2000;Bilkay et al, 2004).…”

Section: Review Of the Literaturementioning

confidence: 99%

A fuzzy dispatching strategy for due-date scheduling of FMSs with information delays

Caprihan

Kumar

Stecke³

2006

Int J Flex Manuf Syst

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Conventional dispatching strategies for FMSs with routing flexibility have typically employed simple heuristics such as work-in-next-queue (WINQ) and number-in-next-queue (NINQ). The effectiveness of these heuristics, however, deteriorates in FMSs whose operational environment must cope with information delays that are non-negligible in comparison to part processing times. Such delays could arise from planned activities, e.g., acquisition, selection, processing, and transfer of plant-wide system status information as well as from unplanned events such as ERP/IT system malfunctions, mismatch of software interfaces, and erroneous inventory master files, for example. Uncertainties from information delays make a strong case for the introduction of fuzzy controllers for making scheduling decisions. This paper introduces a novel fuzzy logic-based dispatching strategy to cope with a specific manifestation of information delays, called status review delay within FMSs. Status review information delays impact system performance adversely because of the obsolescent nature of the information used in the determination of dispatch decisions. A fuzzy dispatching strategy (FDS), designed specifically for deployment within FMSs where information delays are manifest, provides an appropriate alternative to conventional dispatching strategies such as WINQ and NINQ. In the design of an FDS, relevant systembased parameters are fuzzified and an appropriate rule base is designed. Simulation Springer 30 R. Caprihan et al. experiments demonstrate the superiority of an FDS over the conventional WINQ dispatching strategy using the mean tardiness, percent tardy, and mean flowtime performance measures.

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Section: Review Of the Literaturementioning

confidence: 99%

A fuzzy dispatching strategy for due-date scheduling of FMSs with information delays

Caprihan

Kumar

Stecke³

2006

Int J Flex Manuf Syst

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“…The performance of the suggested two-tier control scheme was evaluated using a test environment that is similar in size and scope to environments used in other previous studies on dynamic scheduling such as Talavage (1991, 1994), Chandra and Talavage (1991), Kazerooni et al (1997), Arzi and Iaroslavitz (1999), Subramaniam et al (2000), and Chryssolouris and Subramaniam (2001). The experimental environment in this study consists of six work-centers that can fail from time to time and must be repaired.…”

Section: The Test Environmentmentioning

confidence: 99%

“…Mesghouni et al (1999), Qi et al (2000), Rossi and Dini (2000), and Chryssolouris and Subramaniam (2001) solved the dynamic scheduling problem in FMS using genetic algorithms. Yu et al (1999) and Subramaniam et al (2000) employed fuzzy logic and Trentesaux et al (2000) used intelligent agents to select the appropriate scheduling rule. Other studies used hybrid schemes such as neural networks and inductive learning , fuzzy logic and a genetic algorithm (Fanti et al, 1998), fuzzy logic and simulation (Kazerooni et al, 1997), and finally a combination of learning, intelligent agents, and simulation (Aydin and Oztemel, 2000).…”

Section: Literature Reviewmentioning

confidence: 99%

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Controlling flexible manufacturing systems based on a dynamic selection of the appropriate operational criteria and scheduling policy

Shnits

Sinreich

2006

Int J Flex Manuf Syst

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This study presents the development of a multi-criteria control methodology for flexible manufacturing systems (FMSs). The control methodology is based on a two-tier decision making mechanism. The first tier is designed to select a dominant decision criterion and a relevant scheduling rule set using a rule-based algorithm. In the second tier, using a look-ahead multi-pass simulation, a scheduling rule that best advances the selected criterion is determined. The decision making mechanism was integrated with the shop floor control module that comprises a real-time simulation model at the top control level and RapidCIM methodology at the low equipment control level.A factorial experiment was designed to analyze and evaluate the two-tier decision making mechanism and the effects that the main design parameters have on the system's performance. Next, the proposed control methodology was compared to a selected group of scheduling rules/policies using DEA. The results demonstrated the superiority of the suggested control methodology as well as its capacity to cope with a fast changing environment.

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“…If the problems are small, it is possible to generate optimal schedules using a branch or a bound approach (Brucker et al, 1993). For larger problems, special solution strategies based on priority rules have to be used to ensure execution times of a few minutes (Peres, 1995;Adams et al, 1988;Subramaniam et al, 2000).…”

Section: Literature Reviewmentioning

confidence: 99%

An Approach to Develop a Dynamic Job Shop Scheduling by Fuzzy Rule Based System and Comparative Study with the Traditional Priority Rules

Ahmed¹,

Khan²,

Haque³

et al. 2016

American Journal of Engineering and Applied Sciences

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This paper aims at developing a dynamic job shop scheduling by establishing fuzzy rule based system and comparing its effectiveness with the traditional priority rules. In order to understand the priorities of different jobs in a job shop, the paper investigates all the contributing criteria of different parameters. Since the traditional priority rules only emphasis on a single parameter at a time, the authors propose a method of obtaining a schedule which incorporates all the desired contribution criteria of the parameters used. This method includes establishing a Fuzzy priority rule. Fuzzy is an appropriate model when uncertainty and irregularities are present. It also allows modeling of a significant number of alternatives across different parameters considered in a job shop. Hence, a dynamic job shop schedule can be developed using the established fuzzy priority rule. This research is based on an example of jobs arriving in a regular semi-automated job shop, not a fully automated or software based job shop. The practical implications of this paper is to identify the proper parameters and evaluate their contribution criteria on the required conditions so that managers can determine the proper scheduling and sequence of the jobs to be machined in the job shop. This study provides a deterministic method for local managers to assess the effects of job shop scheduling and sequence of jobs.

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Job Shop Scheduling with Dynamic Fuzzy Selection of Dispatching Rules

Cited by 56 publications

References 26 publications

A fuzzy dispatching strategy for due-date scheduling of FMSs with information delays

A fuzzy dispatching strategy for due-date scheduling of FMSs with information delays

Controlling flexible manufacturing systems based on a dynamic selection of the appropriate operational criteria and scheduling policy

An Approach to Develop a Dynamic Job Shop Scheduling by Fuzzy Rule Based System and Comparative Study with the Traditional Priority Rules

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