2017
DOI: 10.3390/app7010023
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A Genetic Regulatory Network-Based Method for Dynamic Hybrid Flow Shop Scheduling with Uncertain Processing Times

Abstract: Abstract:The hybrid flow shop is a typical discrete manufacturing system. A novel method is proposed to solve the shop scheduling problem featured with uncertain processing times. The rolling horizon strategy is adopted to evaluate the difference between a predictive plan and the actual production process in terms of job delivery time. The genetic regulatory network-based rescheduling algorithm revises the remaining plan if the difference is beyond a specific tolerance. In this algorithm, decision variables wi… Show more

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Cited by 7 publications
(3 citation statements)
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“…This approach enables to respond to problems related to inventory management, production planning, scheduling, location of plants, among others (Chand et al 2002). The use of rolling horizons helps to relax large problems by decomposing them into smaller planning units (Garcia-Sabater et al 2009;Lv et al 2017;Ramezanian et al 2017;Rodriguez et al 2017;Zulkafli and Kopanos 2017). It should be noted that optimal approaches for each horizon act as heuristics and cannot guarantee that the proposed solution is optimum (Karimi et al 2003).…”
Section: Introductionmentioning
confidence: 99%
“…This approach enables to respond to problems related to inventory management, production planning, scheduling, location of plants, among others (Chand et al 2002). The use of rolling horizons helps to relax large problems by decomposing them into smaller planning units (Garcia-Sabater et al 2009;Lv et al 2017;Ramezanian et al 2017;Rodriguez et al 2017;Zulkafli and Kopanos 2017). It should be noted that optimal approaches for each horizon act as heuristics and cannot guarantee that the proposed solution is optimum (Karimi et al 2003).…”
Section: Introductionmentioning
confidence: 99%
“…A branch and price algorithm was applied to solve the model. Lv et al [21] proposed a novel method to solve the shop scheduling problem featured with uncertain processing times. Shan et al [22] utilized the Markov property and neural network ensemble to construct an estimated matrix that combines the interaction of the different local factors.…”
Section: Introductionmentioning
confidence: 99%
“…The last paper [25], by Lv, Zhang, and Qin, deals with dynamic hybrid flow shop scheduling with uncertain processing time by proposing a genetic regulatory network-based rescheduling algorithm. The decision variables are represented by genes in the network and the constraints and certain rescheduling rules are described by regulation equations among genes.…”
mentioning
confidence: 99%