Two-phase neighborhood search algorithm for two-agent hybrid flow shop scheduling problem

Lei, Deming

doi:10.1016/j.asoc.2015.05.027

Cited by 13 publications

(4 citation statements)

References 30 publications

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“…(2014), Figielska (2014), Wang et al. (2015b), Cui and Gu (2015), Lei (2015a), Rahmani and Ramezanian (2016), González‐Neira et al. (2016), Lei and Zheng (2017), Pan et al.…”

Section: An Overview Of Shop Scheduling Problems Characteristicsmentioning

confidence: 99%

Shop scheduling in manufacturing environments: a review

Márquez

Ribeiro

2022

Int Trans Operational Res

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We review the literature about shop scheduling problems in manufacturing systems, revealing the concepts and methodologies that most impact the usage of scheduling theory in manufacturing environments. We focus our attention on the job shop and flow shop problems and their variants. We emphasize the interactions between the scheduling functions and manufacturing paradigms such as Industry 4.0, Computer Integrated Manufacturing, Computer‐Aided Process Planning, Advanced Planning and Scheduling, and Integrated Process Planning and Scheduling. We describe the main components and characteristics of the scheduling ecosystem, and we discuss how the scheduling interacts with the components that make it up and how it is affected by them. The metadata collected from the digital libraries on which the review was based (ScienceDirect, Scopus, and Elsevier) made it possible to characterize the historical evolution of the main concepts of the scheduling ecosystem in terms of scientific publications and research trends in the period 2000–2020.

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“…(2014), Figielska (2014), Wang et al. (2015b), Cui and Gu (2015), Lei (2015a), Rahmani and Ramezanian (2016), González‐Neira et al. (2016), Lei and Zheng (2017), Pan et al.…”

Section: An Overview Of Shop Scheduling Problems Characteristicsmentioning

confidence: 99%

Shop scheduling in manufacturing environments: a review

Márquez

Ribeiro

2022

Int Trans Operational Res

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“…On each segment, operation and its beginning time or completion time are listed, for example, o 22 [1,3] indicates the beginning time [1,3] To calculate makespan, the completion times of J 4 and J 6 are [8,15] and [7,17] and makespan is obtained by max operator of two completion times, so interval makespan is f 1 = [8,17]. For machine M 21 , one idle period exists, the length of period is [2,3], the interval energy consumption on idle period is [3,4.5], energy consumptions for processing three jobs are [6,15], [9,15] and [12,24], respectively and total energy of For the multi-objective optimization problem with the minimization of f 1 , f 2 , Pareto dominance is often used. For solutions x and y, if f i (x) ≤ f i (y) for i = 1, 2 and f i (x) < f i (y) for i = 1 or 2, then x y, which means that x dominates y or y is dominated by x.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Various practical constraints such as preventive maintenance [10], family setup times [11] and assembly [12] are investigated on MOHFSP. Other meta-heuristics are also applied, which include tabu search [10], [13], colonial competitive algorithm (CCA [14]), neighborhood search [12], [15], shuffled frog-leaping algorithm [16] and firefly algorithm [17] etc.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Energy-Efficient Interval Scheduling in Hybrid Flow Shop Using Imperialist Competitive Algorithm

2019

Self Cite

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Energy-efficient hybrid flow shop scheduling problem has attracted much attention in deterministic case; however, uncertainty is seldom considered in previous works. In this paper, energy-efficient interval hybrid flow shop scheduling problem (EIHFSP) is investigated, and a new imperialist competitive algorithm with empire grouping (EGICA) is proposed to minimize total energy consumption and makespan simultaneously. Groups of empires are obtained by defining normalized cost and normalized total cost in interval case, constructing initial empires, and grouping all empires. Assimilation is implemented in a new way, and an adaptive revolution is adopted in each group. Two-phase imperialist competition is newly proposed, and an adaptive search of member from archive is adopted. A number of computational experiments are conducted. The computational results demonstrate that the EGICA has promising advantages on solving the EIHFSP.INDEX TERMS Hybrid flow shop scheduling problem, imperialist competitive algorithm, energy-efficient scheduling, interval processing time.

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“…For more related relevant studies on the multi-agent or two-agent scheduling, the reader may refer to a comprehensive survey by Agnetis et al (2014). For some relevant recent published papers with two-agent setting, we refer readers to Lei (2015), Fan and Cheng (2016), Zhang and Wang (2016), Wan et al (2016), andYin et al (2016a, b).…”

Section: Introductionmentioning

confidence: 99%

Some two-agent single-machine scheduling problems to minimize minmax and minsum of completion times

Cao

et al. 2016

Oper Res Int J

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In this study we address several two-agent problems in which the measure criterion is to minimize the maximum cost or total weighted completion of all the jobs, while subject to an upper bound on the maximum cost of agent A. In term of minimizing the maximum cost of all the jobs subject to an upper bound on the maximum cost of agent A, we discuss some optimal properties and propose polynomial time solution algorithm to solve it. In term of minimizing the total weighted completion of all the jobs subject to an upper bound on the maximum cost of agent A, we analyze the complexity, show that this problem is NP-hard, and discuss it under special cases. In addition, for minimizing the total weighted completion of all the jobs subject to an upper bound on the makespan of agent A, we derive some dominance rules to be used in a branch-and-bound method and propose a heuristic for finding the optimal and nearoptimal solution, respectively. A computational simulation is also provided to determine the performance of the proposed algorithms.

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Two-phase neighborhood search algorithm for two-agent hybrid flow shop scheduling problem

Cited by 13 publications

References 30 publications

Shop scheduling in manufacturing environments: a review

Shop scheduling in manufacturing environments: a review

Multi-Objective Energy-Efficient Interval Scheduling in Hybrid Flow Shop Using Imperialist Competitive Algorithm

Some two-agent single-machine scheduling problems to minimize minmax and minsum of completion times

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