An enhanced NSGA-II algorithm for fuzzy bi-objective assembly line balancing problems

Babazadeh, Hossein; Alavidoost, M.H.; Zarandi, M. H. Fazel; Sayyari, S.T.

doi:10.1016/j.cie.2018.06.014

Cited by 48 publications

(13 citation statements)

References 62 publications

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“…With the emergence and development of heuristics, scholars are also considering the application of more general and intelligent algorithms, such as GA (Ajenblit and Wainwright, 1998; Alavidoost et al, 2015; Babazadeh and Javadian, 2018; Babazadeh et al, 2018; Jonnalagedda and Dabade, 2014; Song and Han, 2002a), PSO (Aydoğan et al, 2016), ACO (Zheng et al, 2017), HA (Nejad et al, 2018; Zhang et al, 2018), GWO (Zhang et al, 2019). Babazadeh et al (2018) and Babazadeh and Javadian (2018) proposed the NSGA-II to solve the fuzzy UALBP, and adopted the same new repair mechanism to make the solutions represented by chromosomes feasible. Aydoğan et al (2016) proposed a modified PSO for the stochastic UALBP, so that to avoid being trapped in a local optimum.…”

Section: Literature Review and Analysismentioning

confidence: 99%

“…With the logistics automation and even the deepening of intelligence, more realistic simulation of machine or human factors, the uncertainty of task time is under consideration. In recent years, research literature on stochastic (Jiao et al, 2020; Liu et al, 2017) and fuzzy (Babazadeh and Javadian, 2018; Babazadeh et al, 2018). ALBPs have appeared continuously.…”

Section: Literature Review and Analysismentioning

confidence: 99%

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Assembly line balance research methods, literature and development review

Jiao

Jin

Xing

et al. 2021

Concurrent Engineering

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With the continuous upgrading of the manufacturing system, the assembly line balancing problem (ALBP) is gradually complicated, and the researches are constantly deepened in the application theory and solution methods. In order to clarify the research direction and development status of assembly line balancing, 89 articles are read and studied. We classify ALBPs to construct the network structure of research from horizontal classification and vertical thinking. The ALBP framework is horizontally given according to the number of models (i.e. the number of products), the layout shape of the assembly line, and the data of task time. The “seven steps for scientific paper” is vertically proposed according to the research steps to comb the research path of scientific and technological literature. The horizontal and vertical extension crosses and constructs the network structure of the ALBP. Any horizontal problem intersects with any step of the vertical “seven steps for scientific paper” to form a research point. We analyze 89 articles according to the development path from the straight line to U-shaped line and then to two-sided U-shaped/parallel U-shaped assembly line, summarize the research algorithm of assembly line balance and count the number of articles, and point out the latest research direction and algorithm development trend of assembly line balance.

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Section: Literature Review and Analysismentioning

confidence: 99%

Section: Literature Review and Analysismentioning

confidence: 99%

Assembly line balance research methods, literature and development review

Jiao

Jin

Xing

et al. 2021

Concurrent Engineering

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“…• Search for prey (p < 0.5and |A| ≥ 1) Whales (search agents) search for prey globally under the guidance of randomly selected agent according to Equations (15)(16)(17)(18).…”

Section: A Basic Woamentioning

confidence: 99%

“…It should be noted that it is difficult to quantify the weights of objectives for the problem under consideration. The Pareto-front optimization [15], [16] probes a set of non-dominated solutions where no objective can be improved without sacrificing others. Each objective in this method has equal importance; while the objectives in this paper show a significant hierarchy relationship owing to their impact on the productivity of the line.…”

Section: Introductionmentioning

confidence: 99%

An Improved Lexicographical Whale Optimization Algorithm for the Type-II Assembly Line Balancing Problem Considering Preventive Maintenance Scenarios

et al. 2020

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In the traditional assembly line balancing, all the workstations are assumed available and hence the unavailability of any workstation brings about the stoppage of the whole line and the waste of the production capacity in the rest workstations. Considering the planning characteristic of preventive maintenance, this paper proposes a novel methodology of integrating the preventive maintenance scenarios into assembly line balancing problems to bypass the unavailable workstation. A lexicographic model is formulated to generate multiple task assignment plans that ensure primarily the high productivity under regular operation scenario and guarantee secondarily the production continuity under preventive maintenance scenarios. And, an improved whale optimization algorithm (IWOA) with three modifications is proposed to solve this problem. Specifically, a combined crossover operator enhances better combination in exploration; three best search agents promote the exploitation; partial regeneration avoids being trapped in local optima. More than five thousand experiments demonstrate that the joint of three modifications endows the IWOA significant superiority over six variants and other six well-known algorithms. Moreover, integrating preventive maintenance scenarios into the assembly line balancing problem increases the production efficiency by 1% at the cost of small production adjustment.

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“…While many studies conducted to cope with the uncertainties in task time for assembly line balancing used stochastic programming and fuzzy logic [1,2,7,8,16], relatively few studies investigated practical applications of robust optimization for dealing with uncertainties in assembly line balancing, in particular U-shaped assembly line, see for example [6,9,11,13,18,20].…”

Section: Literature Reviewmentioning

confidence: 99%

Robust optimization for U-shaped assembly line worker assignment and balancing problem with uncertain task times

Yılmaz¹

2020

Cro. Oper. Res. Rev.

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Awareness of the importance of U-shaped assembly line balancing problems is all on the rise. In the U-shaped assembly line, balancing is affected by the uncertainty associated with the assembly task times. Therefore, it is crucial to develop an approach to respond to the uncertainty caused by the task times. When the great majority of existing literature related to uncertainty in the assembly line is considered, it is observed that the U-shaped assembly line balancing problem under uncertainty is scarcely investigated. That being the case, we aim to fill this research gap by proposing a robust counterpart formulation for the addressed problem. In this study, a robust optimization model is developed for the U-shaped assembly line worker assignment and balancing problem (UALWABP) to cope with the task time uncertainty characterized by a combined interval and polyhedral uncertainty set. A real case study is conducted through data from a company producing water meters.

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An enhanced NSGA-II algorithm for fuzzy bi-objective assembly line balancing problems

Cited by 48 publications

References 62 publications

Assembly line balance research methods, literature and development review

Assembly line balance research methods, literature and development review

An Improved Lexicographical Whale Optimization Algorithm for the Type-II Assembly Line Balancing Problem Considering Preventive Maintenance Scenarios

Robust optimization for U-shaped assembly line worker assignment and balancing problem with uncertain task times

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