A novel memetic ant colony optimization-based heuristic algorithm for solving the assembly line part feeding problem

Fathi, Masood; Rodríguez, Victoria María Sueiro; Álvarez, Mario

doi:10.1007/s00170-014-6068-0

Cited by 35 publications

(23 citation statements)

References 47 publications

(55 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The problem was an extension of Fathi, Alvarez, and Rodríguez (2014b), which is based on the problem faced by VW-Navarra. The ALPFP consists of two sub-problems, namely tour scheduling and tow-train loading problems.…”

Section: Discussionmentioning

confidence: 99%

“…The original problem was solved using a simulated annealing algorithm and the results compared favourably to those obtained by CPLEX. A first extension to this problem was studied in Fathi, Alvarez, and Rodríguez (2014b) by also considering a constraint on tour delivery time. A memetic ant colony-based heuristic algorithm (MACO) was proposed and the solutions obtained were compared with those of CPLEX.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines

Fathi

Rodríguez

Fontes

et al. 2015

International Journal of Production Research

Self Cite

View full text Add to dashboard Cite

The Assembly Line Part Feeding Problem (ALPFP) is a complex combinatorial optimisation problem concerned with the delivery of the required parts to the assembly workstations in the right quantities at the right time. Solving the ALPFP includes simultaneously solving two sub-problems, namely tour scheduling and tow-train loading. In this article, we first define the problem and formulate it as a multi-objective mixed-integer linear programming model. Then, we carry out a complexity analysis, proving the ALPFP to be NP-complete. A modified particle swarm optimisation (MPSO) algorithm incorporating mutation as part of the position updating scheme is subsequently proposed. The MPSO is capable of finding very good solutions with small time requirements. Computational results are reported, demonstrating the efficiency and effectiveness of the proposed MPSO.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines

Fathi

Rodríguez

Fontes

et al. 2015

International Journal of Production Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Fathi et al [28] tackled the part feeding problem at the assembly line by proposing a mathematical model and an ant colony optimization algorithm (ACO). The study attempted to find the best sequence and quantity of parts to be loaded on tugger trains on fixed routes and with cyclic delivery trips.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Emde et al [24] PSSP a Golz et al [15] OH b Emde and Boysen [25] DP Rao et al [26] GASA Faccio et al [27] Simulation Fathi et al [28] ACO Fathi et al [29] SA Muguerza et al [30] Fathi et al [31] PSO Emde and Schneider [32] NSA Peng and Zhou [33] HACO Zhou and Shen [9] TS PSO Zhou and Peng [34] OH & PSSP a Problem-specific solution procedure; b Other heuristics.…”

Section: Model Scheduling Loading Routingmentioning

confidence: 99%

Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization

Fathi

Ghobakhloo

2020

Sustainability

Self Cite

View full text Add to dashboard Cite

The fourth industrial revolution and the digital transformation of consumer markets require contemporary manufacturers to rethink and reshape their business models to deal with the ever-changing customer demands and market turbulence. Manufacturers nowadays are inclined toward product differentiation strategies and more customer-focused approaches to stay competitive in the Industry 4.0 environment, and mass customization and product diversification are among the most commonly implemented business models. Under such circumstances, an economical material supply to assembly lines has become a significant concern for manufacturers. Consequently, the present study deals with optimizing the material supply to mixed-model assembly lines that contribute to the overall production cost efficiency, mainly via the reduction of both the material transportation and material holding costs across production lines, while satisfying certain constraints. Given the complexity of the problem, a novel two-stage heuristic algorithm is developed in this study to enable a cost-efficient delivery. To assess the efficiency and effectiveness of the proposed heuristic algorithm, a set of test problems are solved and compared against the best solution found by a commercial solver. The results of the comparison reveal that the suggested heuristic provides reasonable solutions, thus offering immense opportunities for production cost efficiency and manufacturing sustainability under the mass customization philosophy.

show abstract

“…3.4 启发信息函数的设计启发函数可以看成人工蚂蚁对自身环境的一种选择，或者说是人工蚂蚁自身的经验函数，启发函数对蚂蚁的路径选择起到启发引导的作用，构建合理的信息启发函数是算法获得成功的关键因素 [15] 。本文根据再制造优化选配目标的需求，定义了一种计算启发信息的方法，为了减少再制造产品质量的波动，通过考虑已被选入装配尺寸链的零件对质量损失函数的贡献，定义的启发函数如下式 …”

unclassified

Research on Selective Assembly Method Optimization for Construction Machinery Remanufacturing Based on Ant Colony Algorithm

Su¹,

Xiao-hong²,

Yinghui³

et al. 2017

JME

View full text Add to dashboard Cite

Abstract：In view of the problems of low assembly efficiency, poor assembly precision and many remaining unmatched parts in the construction machinery remanufacturing, an optimal selective assembly method for remanufacturing is put forward. By analyzing the uncertainty factors and the influence factors on the assembly quality in the construction machinery remanufacturing, a new model is built based on the multivariate quality loss function and the assembly deviation. Considering the characteristics that the remanufactured parts and reused parts should be utilized preferentially and the remaining unmatched parts should be reduced under the condition of satisfying the accuracy of assembly, an assembly success rate and a remanufacturing resource utilization rate are presented as the assembly quality evaluation indexes. Thus, a comprehensive selective assembly model for improving the remanufacturing assembly accuracy and the remanufacturing resource utilization can be formed. Based on the characteristics of remanufacturing selective assembly model, the pheromone update strategy is improved and the heuristic function of the ant colony algorithm is designed, which are helpful to gain optimal assembly combinations and reduce the influence of the uncertainty factors on the quality of the assembly. The crank and connecting rod mechanism assembly of a remanufactured engine verifies that the method is feasible and effective.

show abstract

A novel memetic ant colony optimization-based heuristic algorithm for solving the assembly line part feeding problem

Cited by 35 publications

References 47 publications

A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines

A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines

Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization

Research on Selective Assembly Method Optimization for Construction Machinery Remanufacturing Based on Ant Colony Algorithm

Contact Info

Product

Resources

About