No-wait flowshop scheduling problem with two criteria; total tardiness and makespan

Allahverdi, Ali; Aydilek, Harun; Aydilek, Asiye

doi:10.1016/j.ejor.2017.11.070

Cited by 46 publications

(18 citation statements)

References 36 publications

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“…Allahverdi and Aydilek [34] generated different versions of insertion in genetic algorithm in the no-wait flow shop to minimize TCT and C max . Allahverdi et al [2] proposed an algorithm that was a combination of simulated annealing and insertion algorithm for solving the no-wait flow shop scheduling problem with two criteria: total tardiness and C max .…”

Section: Literature Reviewmentioning

confidence: 99%

“…While some parts are processed in a certain machines, others might be skipped those machines. In a no-wait flow shop scheduling problem, a certain process of a job needs to be conducted uninterruptedly from the beginning of the process to the end of the process [2]. No-wait scheduling has many applications in real-world such as flight, train, and surgery problems.…”

Section: Introductionmentioning

confidence: 99%

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A hybrid genetic local and global search algorithm for solving no-wait flow shop problem with bi criteria

Keskin

Engin

2021

SN Appl. Sci.

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This paper addresses the m-machine no-wait Flow Shop Scheduling with Setup Times (NW-FSSWST). Two performance measures: total flow time and makespan are considered. The objective is to find a sequence that minimizing total flow time ($$\sum C_{j}$$ ∑ C j ) and makespan ($$C_{j}$$ C j ) simultaneously. A Hybrid Genetic Local and Global Search Algorithm (HGLGSA) is proposed to solve the NW-FSSWST for two performance criteria. The hybrid genetic algorithm is constructed by insert-search and self-repair algorithm with self-repair function. The proposed HGLGSA is tested on 192 benchmark problems of NW-FSSWST in the literature. A full factorial experimental design is made for determined the best parameter sets that improve the performance of the proposed algorithm. The computational results are compared with the benchmark solutions from the literature. The experimental results demonstrate the effectiveness and efficiency of the proposed HGLGSA for solving NW-FSSWST.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A hybrid genetic local and global search algorithm for solving no-wait flow shop problem with bi criteria

Keskin

Engin

2021

SN Appl. Sci.

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“…Manufacturing systems have become progressively more complex and the market requires higher levels of adaptability and customization, demanding for a more effective production management. The traditional aim for industrial scheduling applications was the minimization of the total makespan (Allahverdi et al 2018;Bagheri et al 2010;Eddaly et al 2016;Gonzalez-Neira et al 2017;Hatami et al 2018;Juan et al 2014;Pan and Wang 2012); however, more recently, other performances have been taken into the optimization objectives, leading to cost minimization, to total tardiness minimization and others (Behnamian and Zandieh 2011;Fig. 1 Role of DT to support the control of manufacturing operations in cyber-physical production systems Zhang et al 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Field-synchronized Digital Twin framework for production scheduling with uncertainty

et al. 2020

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Research on scheduling problems is an evergreen challenge for industrial engineers. The growth of digital technologies opens the possibility to collect and analyze great amount of field data in real-time, representing a precious opportunity for an improved scheduling activity. Thus, scheduling under uncertain scenarios may benefit from the possibility to grasp the current operating conditions of the industrial equipment in real-time and take them into account when elaborating the best production schedules. To this end, the article proposes a proof-of-concept of a simheuristics framework for robust scheduling applied to a Flow Shop Scheduling Problem. The framework is composed of genetic algorithms for schedule optimization and discrete event simulation and is synchronized with the field through a Digital Twin (DT) that employs an Equipment Prognostics and Health Management (EPHM) module. The contribution of the EPHM module inside the DT-based framework is the real time computation of the failure probability of the equipment, with data-driven statistical models that take sensor data from the field as input. The viability of the framework is demonstrated in a flow shop application in a laboratory environment.

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“…Sum of the makespan measure, and total weighted tardiness [101], as well as makespan and total completion time [101], are among the multi-objective NWFSPs solved considering a priori preference articulation. Alternatively, some other studies developed multi-objective optimization algorithms under a posterior preference articulation to solve the NWFSP addressing conflicting objectives, like makespan and total tardiness [102,103]; makespan and maximum lateness [104].…”

Section: Literature Reviewmentioning

confidence: 99%

Improved Beam Search for Optimizing No-Wait Flowshops With Release Times

et al. 2020

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Production management of perishable goods is highly complex and requires well-informed decisions in corresponding stages. In such production environments, scheduling problems with time constraints are of high relevance to ensure the timely flow of the work-in-process material and goods. This study introduces the no-wait flowshop scheduling problem with release times (NWFSP-RT) to help advance decision support systems in the food production industry. For this purpose, an original mixed-integer linear programming (MILP) formulation is proposed for minimizing the makespan. Since Beam Search (BS) algorithm has been successfully applied to solve various scheduling problems, a BS algorithm, and an improved variant, the local search-based Beam Search (BSLS) algorithms are developed to solve the NWFSP-RT problem. Extensive numerical analysis is conducted to analyze the performance of the algorithms in solving this highly intractable extension of the scheduling problems. We showed that BSLS effectively avoids early convergence and local optimality while dismissing non-promising search directions within a partial enumeration solution approach. The statistical analysis confirmed that the improved BS algorithm performs better in terms of solution quality. Applications of the developed heuristic are worthwhile research topics to pursue in solving other complex optimization problems. INDEX TERMS Flowshop scheduling, no-wait, release time, Beam Search.

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No-wait flowshop scheduling problem with two criteria; total tardiness and makespan

Cited by 46 publications

References 36 publications

A hybrid genetic local and global search algorithm for solving no-wait flow shop problem with bi criteria

A hybrid genetic local and global search algorithm for solving no-wait flow shop problem with bi criteria

Field-synchronized Digital Twin framework for production scheduling with uncertainty

Improved Beam Search for Optimizing No-Wait Flowshops With Release Times

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