Assignment of collaborators to multiple business problems using genetic algorithm
- Authors
- Choi, Keunho; Kim, Gunwoo; Suh, Yongmoo; Yoo, Donghee
- Issue Date
- 11월-2017
- Publisher
- SPRINGER HEIDELBERG
- Keywords
- Collaborator selection; Problem solving; Genetic algorithm; Optimization
- Citation
- INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT, v.15, no.4, pp.877 - 895
- Indexed
- SSCI
SCOPUS
- Journal Title
- INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT
- Volume
- 15
- Number
- 4
- Start Page
- 877
- End Page
- 895
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/81726
- DOI
- 10.1007/s10257-016-0328-5
- ISSN
- 1617-9846
- Abstract
- As firms encounter new problems in the fast-changing business environment, they have to find collaborators with problem-solving expertise. Since this optimization problem takes place in a firm as the business environment changes, genetic algorithm (GA), which has shown outstanding performance in obtaining a sub-optimal solution relatively quickly, seems to be the right solution, one that is superior to goal-programming, multi-attribute decision making, and branch and bound. We therefore propose a GA-based approach to solving the problem of assigning collaborators to multiple business problems. Our solution worked well in several experiments.
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Collections - Korea University Business School > Department of Business Administration > 1. Journal Articles
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