Comparative study of simulated annealing, genetic algorithms and tabu search for solving binary and comprehensive machine-grouping problems
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Publication:4810048
DOI10.1080/00207540210131851zbMath1044.90506OpenAlexW2076370349MaRDI QIDQ4810048
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Publication date: 31 August 2004
Published in: International Journal of Production Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207540210131851
Abstract computational complexity for mathematical programming problems (90C60) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59) Production models (90B30)
Related Items (9)
An efficient exact model for the cell formation problem with a variable number of production cells ⋮ Fractional factorial analysis to the configuration of simulated annealing applied to the multi-objective optimization of master production scheduling problems ⋮ A new and practical heuristic for Master Production Scheduling creation ⋮ Tabu search approach based on a similarity coefficient for cell formation in generalized group technology ⋮ A new multi-objective optimization method for master production scheduling problems using simulated annealing ⋮ An ant colony optimization metaheuristic for machine-part cell formation problems ⋮ Group technology by an ant system algorithm ⋮ Design of cellular manufacturing systems using a genetic algorithm method ⋮ A fuzzy goal-programming model of machine-tool selection and operation allocation problem in FMS: a quick converging simulated annealing-based approach
Cites Work
- Optimization by Simulated Annealing
- Cell formation in manufacturing systems through simulated annealing: An experimental evaluation
- A close neighbour algorithm for designing cellular manufacturing systems
- An ideal seed non-hierarchical clustering algorithm for cellular manufacturing
- ZODIAC—an algorithm for concurrent formation of part-families and machine-cells
- The minimum-cost, machine-part cell formation problem
- Manufacturing cell formation in the presence of lot splitting and multiple units of the same machine
- A multi-constraint neural network for the pragmatic design of cellular manufacturing systems
- A simulated annealing solution to the cell formation problem
- Jointly solving the group scheduling and machining speed selection problems: A hybrid tabu search and simulated annealing approach
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