A review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches

Rashid, Mohd Fadzil Faisae Ab; Hutabarat, Windo; Tiwari, Ashutosh

doi:10.1007/s00170-011-3499-8

Cited by 178 publications

(86 citation statements)

References 89 publications

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“…Since the first formulation of an ALBP by Salveson (1955), various extensions have been investigated, and many attempts have been made to fill out the gap between academic research and real-life applications. For detailed reviews of research on ALBPs, see Scholl and Becker (2006); Becker and Scholl (2006); Boysen et al (2007); Tasan and Tunali (2008); Rashid et al (2012); Hazır et al (2014); Sivasankaran and Shahabudeen (2014).…”

Section: Introductionmentioning

confidence: 98%

“…As a relatively new algorithm, not many papers applying Particle swarm optimization (PSO) to ALBPs have been published, much less for seeking a set of Pareto-optimal solutions for the MOO of assembly lines (Rashid et al 2012). Therefore, this paper addresses the bi-criteria stochastic assembly line balancing problem (BSALBP) with flexible task times and zoning constraints, which aims at simultaneously minimizing the cycle time and the equipment cost, and intends to propose a novel PSO algorithm to search a group of Pareto-optimal solutions.…”

Section: Introductionmentioning

confidence: 99%

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A hybrid PSO/SA algorithm for bi-criteria stochastic line balancing with flexible task times and zoning constraints

2015

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This paper addresses a stochastic assembly line balancing problem with flexible task times and zoning constraints. In this problem, task times are regarded as interval variables with given lower and upper bounds. Machines can compress processing times of tasks to improve the line efficiency, but it may increase the equipment cost, which is defined via a negative linear function of task times. Thus, it is necessary to make a compromise between the line efficiency and the equipment cost. To solve this problem, a bi-objective chance-constrained mixed 0-1 programming model is developed to simultaneously minimize the cycle time and the equipment cost. Then, a hybrid Particle swarm optimization algorithm is proposed to search a set of Pareto-optimal solutions, which employs the simulated annealing as a local search strategy. The Taguchi method is used to investigate the influence of parameters, and accordingly a suitable parameter setting is suggested. Finally, the comparative results show that the proposed algorithm outperforms the existing algorithms by obtaining better solutions within the same running time.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

A hybrid PSO/SA algorithm for bi-criteria stochastic line balancing with flexible task times and zoning constraints

2015

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“…Furthermore, considering the background of Industry 4.0 [3], the study of ASP turns out to be particularly crucial. ASP is one of the main sub-problems of the broader assembly planning (AP) problem [4], and it is also a NP-hard problem [5], with the purpose of obtaining a sequence of assembly motions to meet the process requirements at minimum costs. In general, solving of ASP problem can be divided into two aspects, namely assembly modeling and problem solving algorithm.…”

Section: Introductionmentioning

confidence: 99%

Assembly sequence planning based on an improved harmony search algorithm

Qin

Zeng

et al. 2015

Int J Adv Manuf Technol

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As a typical, discrete, and NP-hard problem, assembly sequence planning (ASP) has direct impact on assembly quality and costs. So far, lots of graph-based and meta-heuristic approaches cannot solve this problem effectively. This paper proposes an effective ASP algorithm based on the harmony search (HS) algorithm, which has an outstanding global search ability to obtain the global optimum more efficiently. To solve the ASP problem, an improved harmony search (IHS) algorithm is proposed mainly in four aspects: (1) an encoding of harmony is designed based on ASP problems; (2) an initial harmony memory (HM) is established using the opposition-based learning (OBL) strategy; (3) a particular way to improvise a new harmony is developed; and (4) a local search strategy is introduced to accelerate the convergence speed. Finally, the advantage of the proposed ASP algorithm over the competing algorithms in solving ASP problems is verified by two experiments. Moreover, the proposed ASP algorithm is applied to a practical problem, a propeller of azimuth thruster to verify its practicability.

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“…In the past decades, geometric feasibility reasoning approach [3][4][5][6], knowledge-based approach [7][8][9][10][11][12][13] and intelligent optimization method were presented to deal with the problem of ASP. As described in the survey of [14] and [15], to avoid the combinatorial explosion, more and more research in the domain of assembly sequence planning focused on the methods of intelligent optimization and the combination approaches.…”

Section: Introductionmentioning

confidence: 99%

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The modified firefly algorithm considering fireflies’ visual range and its application in assembly sequences planning

Zhang

Zeng

et al. 2015

Int J Adv Manuf Technol

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This paper proposes a modified discrete firefly algorithm (MDFA) to solve the problem of assembly sequence planning. Firstly, to improve the performance of the firefly algorithm (FA), we proposed a MDFA by endowing the fireflies with the capability of changeable visual range. The computing case shows the proposed algorithm is more effective and robust than standard FA, genetic algorithm and particle swarm optimization algorithm. Secondly, a method of how to set parameters for FA and MDFA is proposed. This method is practical in the application of FA to solve discrete problem. Thirdly, to make the sequences more closer to real industrial requirements, a so called process precedence relations (PPR) evaluation function is presented, which not only considering the interference between parts, assembly tools and clamps, but also regarding the assembly order between parts and their reference parts. Finally, the evolution performance of the MDFA is investigated, and the performance of the proposed approach to solve ASP is verified through two cases study.

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A review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches

Cited by 178 publications

References 89 publications

A hybrid PSO/SA algorithm for bi-criteria stochastic line balancing with flexible task times and zoning constraints

A hybrid PSO/SA algorithm for bi-criteria stochastic line balancing with flexible task times and zoning constraints

Assembly sequence planning based on an improved harmony search algorithm

The modified firefly algorithm considering fireflies’ visual range and its application in assembly sequences planning

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