Multi-objective optimization algorithms for flow shop scheduling problem: a review and prospects

Sun, Yu; Zhang, Chaoyong; Gao, Liang; Wang, Xiaojuan

doi:10.1007/s00170-010-3094-4

Cited by 88 publications

(41 citation statements)

References 113 publications

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“…Among different methods, we can highlight the algorithms proposed by Palmer (1965), Campbell et al (1970 and Nawaz et al (1983). , Vallada et al (2008) and Pan and Ruiz (2013) presented extensive reviews for FS and PFS problems with single objective functions, while Sun et al (2010) and Yenisey and Yagmahan (2014) applied it for multi-objective FS problems. Although, evaluated 25 heuristics and metaheuristics for makespan minimization.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Also Pan and Ruiz (2013) compared 22 existing heuristics to minimize the flowtime and proposed five new methods to solve the problem. On the other hand, the reviews of Sun et al (2010) and Yenisey and Yagmahan (2014), in spite of presenting a multiobjective FS literature survey, mentioned few works dealt with weighted tardiness as one of the objectives assessed and also no review was found in TWT minimization. …”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

GRASP to minimize total weighted tardiness in a permutation flow shop environment

Molina-Sánchez¹,

González-Neira²

2016

10.5267/j.ijiec

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This paper addresses the scheduling problem in a Permutation Flow Shop (PFS) environment, which is associated with many types of industries such as chemical, petrochemical, automobile manufacturing, metallurgical, textile, etc. Thus, this work intends to solve a PFS scheduling problem in order to minimize the total weighted tardiness, since it is an important sequencing criterion not only for on time delivery jobs but also for customer satisfaction. To solve the problem, GRASP (Greedy Randomized Adaptive Search Procedure) metaheuristic is proposed as a solution, which has shown competitive results compared with other combinatorial problems. In addition, two utility functions called Weighted Modified Due Date (WMDD) and Apparent Tardiness Cost (ATC) are proposed to develop GRASP. These are based on dynamic dispatching rules and also known for solving the problem of total weighted tardiness for single machine scheduling problem. Next, an experimental design was carried out for comparing the GRASP performance with both utility functions and against the WEDD dispatching rule results. The results indicate that GRASP-WMDD could improve the total weighted tardiness in 47.8% compared with WEDD results. Finally, the GRASP-WMDD performance for the PFS total tardiness problem was evaluated, obtaining a relative deviation index of 13.89% and ranking the method over 26 heuristics and metaheuristics.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

GRASP to minimize total weighted tardiness in a permutation flow shop environment

Molina-Sánchez¹,

González-Neira²

2016

10.5267/j.ijiec

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show abstract

“…Since the first HFS problem was described by Salvador [10], vast amounts of academic work have been carried out on HFS scheduling due to its complexity and practical relevance [11][12][13][14][15]. Different kinds of methods (e.g., exact methods, heuristics and metaheuristics) were proposed to minimize a variety of objectives, which include the maximum completion time, the maximum flow time, the number of late jobs [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A Genetic Regulatory Network-Based Method for Dynamic Hybrid Flow Shop Scheduling with Uncertain Processing Times

Zhang

Qin

2017

Applied Sciences

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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 within the rolling horizon are represented by genes in the network. The constraints and certain rescheduling rules are described by regulation equations between genes. The rescheduling solutions are generated from expression procedures of gene states, in which the regulation equations convert some genes to the expressed state and determine decision variable values according to gene states. Based on above representations, the objective of minimizing makespan is realized by optimizing regulatory parameters in regulation equations. The effectiveness of this network-based method over other ones is demonstrated through a series of benchmark tests and an application case collected from a printed circuit board assembly shop.

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“…However, in practical applications, there are many objectives that have been considered in scheduling problems. This has indicated that evaluating a single objective is not satisfactory for improving the performance of the complete manufacturing systems [29]. In addition, satisfying a single objective cannot resolve the trade-off between criteria.…”

Section: Introductionmentioning

confidence: 99%

Reentrant FMS scheduling in loop layout with consideration of multi loading-unloading stations and shortcuts

Rifai

Dawal

Zuhdi

et al. 2015

Int J Adv Manuf Technol

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The scheduling problem in flexible manufacturing systems (FMS) environment with loop layout configuration has been shown to be a NP-hard problem. Moreover, the improvement and modification of the loop layout add to the difficulties in the production planning stage. The introduction of multi loading-unloading points and turntable shortcut resulted on more possible routes, thus increasing the complexity. This research addressed the reentrant FMS scheduling problem where jobs are allowed to reenter the system and revisit particular machines. The problem is to determine the optimal sequence of the jobs as well as the routing options. A modified genetic algorithm (GA) was proposed to generate the feasible solutions. The crowding distance-based substitution was incorporated to maintain the diversity of the population. A set of test was applied to compare the performance of the proposed approach with other methods. Further computational experiments were conducted to assess the significance of multi loading-unloading and shortcuts in reducing the makespan, mean flow time, and tardiness. The results highlighted that the proposed model was robust and effective in the scheduling problem for both small and large size problems.

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Multi-objective optimization algorithms for flow shop scheduling problem: a review and prospects

Cited by 88 publications

References 113 publications

GRASP to minimize total weighted tardiness in a permutation flow shop environment

GRASP to minimize total weighted tardiness in a permutation flow shop environment

A Genetic Regulatory Network-Based Method for Dynamic Hybrid Flow Shop Scheduling with Uncertain Processing Times

Reentrant FMS scheduling in loop layout with consideration of multi loading-unloading stations and shortcuts

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