- Title
- Grouping genetic algorithm for industrial engineering applications
- Creator
- Mutingi, Michael, Mapfaira, Herbert, Dube, Partson
- Subject
- Grouping problems, Grouping genetic algorithms, Genetic algorithms, Metaheuristics, Industrial engineering
- Date
- 2013
- Type
- Article
- Identifier
- uj:4734
- Identifier
- http://hdl.handle.net/10210/11560
- Description
- Industry is inundated with grouping problems concerned with formation of groups or clusters of system entities for the purpose of improving the overall system efficiency and effectiveness. Various extant grouping problems include cell formation problem, vehicle routing problem, bin packing problem, truck loading, home healthcare scheduling, and task assignment problem. Given the widespread grouping problems in industry, it is important to develop a tool for solving such problems from a common view point. This paper seeks to identify common grouping problems, identify their common grouping structures, present an outline of group genetic algorithm (GGA), and map the problems to the GGA approach. The practicality of the GGA tool in is highly promising in Industrial Engineering applications.
- Publisher
- BIE
- Rights
- © 2013, Authors & BIE
- Full Text
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