Multi-objective optimization of manufacturing cell design

DOI10.1080/00207540600620773zbMath1114.90458OpenAlexW1977001096MaRDI QIDQ3430255

C. Dimopoulos

Publication date: 21 March 2007

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207540600620773

zbMATH Keywords

multi-objective optimizationevolutionary computationgenetic programmingNSGA-IIcellular manufacturingcell-formation problem

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59) Production models (90B30)

Related Items (5)

Optimal feeding profile in fed-batch bioreactors using a genetic algorithm ⋮ Optimisation of a multi-objective two-dimensional strip packing problem based on evolutionary algorithms ⋮ Radio frequency identification system optimisation models for lifecycle of a durable product ⋮ The modified fuzzy art and a two-stage clustering approach to cell design ⋮ Hybrid organization of functional departments and manufacturing cells in the presence of imprecise data

Uses Software

• SPEA2

Cites Work

• Efficient solutions to the cell-formation problem with multiple routings via a double-loop genetic algorithm
• Investigating the use of genetic programming for a classic one-machine scheduling problem
• A hierarchical clustering methodology based on genetic programming for the solution of simple cell-formation problems
• A genetic algorithm-based approach to cell composition and layout design problems
• The minimum-cost, machine-part cell formation problem
• Solving cell formation problems in a manufacturing environment with flexible processing and routeing capabilities
• A genetic algorithm for manufacturing cell formation with multiple routes and multiple objectives
• Empirical findings on manufacturing cell design
• A review of the modern approaches to multi-criteria cell design
• A multi-objective genetic algorithm approach to the design of cellular manufacturing systems
• Evolving knowledge for the solution of clustering problems in cellular manufacturing

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