Minimising makespan in the two-stage assembly hybrid flow shop scheduling problem using artificial immune systems

Komaki, G.M.; Teymourian, Ehsan; Kayvanfar, Vahid

doi:10.1080/00207543.2015.1035815

Cited by 71 publications

(25 citation statements)

References 25 publications

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“…Belaid et al (2012) use a greedy algorithm, a novel ant colony optimization with features of simulated annealing (taken from T'kindt et al (2002)) and a dedicated heuristic to solve a practical case in the shampoo industry. For further examples of holistic heuristics, we refer to Komaki et al (2016), Lei and Guo (2016) and Liu et al (2017). Decomposition strategies have also been used to break up the scheduling of a hybrid flow shop into independent stages.…”

Section: Literature Reviewmentioning

confidence: 99%

Scheduling hybrid flow shops with time windows

Yang

Leus

2019

J Heuristics

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Hybrid flow shops can be encountered in various industrial settings. In this paper we develop methods for scheduling hybrid flow shops with hard time windows. Specifically, we study a two-stage hybrid flow shop scheduling problem with time windows to minimize the total weighted completion times. Each stage consists of one or more identical parallel machines, and each job visits two processing stages in series. Finding a feasible schedule with hard time windows is a challenging task in this setting, because it is NP-complete in the strong sense even for a single machine in a single stage. We propose two matheuristics to find an initial feasible solution by local branching. We also develop two schedule improvement procedures, one based on stage-by-stage decomposition, and one using adapted local branching. The performance of our methods is validated via extensive computational experiments.

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Section: Literature Reviewmentioning

confidence: 99%

Scheduling hybrid flow shops with time windows

Yang

Leus

2019

J Heuristics

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“…Komaki et al [10] proposed an artificial immune system algorithm (AIS) to solve a two-stage hybrid flow shop followed by a single assembly machine to minimize the makespan and Deng et al [11] proposed a competitive memetic algorithm (CMA) to minimize the makespan in a parallel-manufacturing machine and a single assembly machine in TSASP. Komaki and Kayvanfar [12] proposed a grey wolf optimizer algorithm to solve the TSASP with release time in a parallel-manufacturing machine and a single assembly machine. Jung et al [13] proposed two hybrid genetic algorithms (HGAs) for twostage assembly scheduling problem (TSASP) for processing products with dynamic-component sizes and a setup time.…”

Section: Introductionmentioning

confidence: 99%

Two-Stage Assembly Scheduling with Batch Setup Times, Time-Dependent Deterioration, and Preventive Maintenance Activities Using Meta-Heuristic Algorithms

Jung

Woo

Koh

et al. 2018

Mathematical Problems in Engineering

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This article considers a two-stage assembly scheduling problem (TSASP) with batch setup times, time-dependent deterioration, and preventive maintenance activities (PMAs). The objective of this problem is to simultaneously determine the optimal component-manufacturing sequence (CMS), product-assembly sequence (PAS), number of setups, and number and position of PMAs (PPMA). First, to determine the optimal solution, a novel mixed integer linear programming model (MILP) for the proposed problem is derived. Then, a standard genetic algorithm (SGA), hybrid genetic algorithm (HGA), standard harmony search (SHS), hybrid harmony search (HHS), and harmony-search-based evolutionary algorithm (HSEA) were proposed owing to the intractability of the optimal solution for large-scale problems. SGA and SHS provide a chromosome to represent a complete solution including three decisions (CMS, PAS, and PPMA). HGA, HHS, and HSEA provide a chromosome to represent a partial solution including PAS. CMS and PPMA are found by an effective local search heuristic based on the partial solution. A computational experiment is then conducted to evaluate the impacts of the factors on the performance of the proposed algorithms.

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“…Sci. 2017, 7, 23 6 of 19 the rescheduling problem based on S(l) once the reactive scheduling is regarded as necessary. The rescheduling algorithm solves this problem without interrupting the ongoing operations and then generates a new predictive plan based on CS(l) and ES(l), as shown in Figure 3.…”

Section: Event-driven Rescheduling Strategymentioning

confidence: 99%

“…Wang et al [22] proposed a branch-and-bound algorithm to investigate the two-stage HFS scheduling problem in a no-wait environment. Komaki et al [23] developed several algorithms featured with a new lower In a HFS scheduling problem, the binary decision variable is similar to the state of a gene. The decision variable interaction in constraints and objectives has an analogous form with gene regulations.…”

Section: Introductionmentioning

confidence: 99%

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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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Minimising makespan in the two-stage assembly hybrid flow shop scheduling problem using artificial immune systems

Cited by 71 publications

References 25 publications

Scheduling hybrid flow shops with time windows

Scheduling hybrid flow shops with time windows

Two-Stage Assembly Scheduling with Batch Setup Times, Time-Dependent Deterioration, and Preventive Maintenance Activities Using Meta-Heuristic Algorithms

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

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