Optimisation of partner selection and collaborative transportation scheduling in Virtual Enterprises using GA |
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| Affiliation: | 1. Department of Engineering, University of Almería, 04120 Almería, Spain;2. Department of Informatics, University of Almería, 04120 Almería, Spain;3. Facultad de Ingenería, Universidad Veracruzana, Campus Coatzacoalcos, Coatzacoalcos, Mexico;1. Pontificia Universidad Católica de Valparaíso, Avenida Brasil 2950, Valparaíso, Chile;2. Universidad Finis Terrae, Av. Pedro de Valdivia 1509, Santiago, Chile;3. Universidad de Playa Ancha, Av. Leopoldo Carvallo 270, Valparaíso, Chile;4. Universidad Autónoma de Chile, Pedro de Valdivia 641, Santiago, Chile;5. CNRS, LINA, University of Nantes, 2 rue de la Houssinière, Nantes, France;6. Escuela de Ingeniería Industrial, Universidad Diego Portales, Manuel Rodríguez Sur 415, Santiago, Chile;1. Department of Systems Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenu, Kowloon Tong, Hong Kong;2. Centre for Systems Informatics Engineering, City University of Hong Kong, 83 Tat Chee Avenu, Kowloon Tong, Hong Kong;3. School of Management, Hefei University of Technology, Hefei, Box 270, Hefei 230009, Anhui, PR China;4. Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, Box 270, Hefei 230009, Anhui, PR China;1. Department of Electrical and Computer Engineering, University of Macau, Avenida Padre Tomas Pereira, Taipa, Macau;2. Department of Computer Science, Huizhou University, Huizhou 516007, China |
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| Abstract: | Partner selection and transportation scheduling are critical to the success of a Virtual Enterprise. Collaborative transportation is a promising strategy that can help many enterprises survive and thrive in today’s highly competitive market. To help decision makers establish and operate Virtual Enterprises more effectively, an innovative decision support system is proposed in this paper. First, new model for integration of partner selection and collaborative transportation scheduling in Virtual Enterprises is developed. This integrated optimisation problem is very dynamic in nature and it is required to optimise a number of interlinked sub-problems at the same time. Then, a novel Genetic Algorithm with a unique dynamic chromosome representation and genetic operations is developed to find an optimal solution to the integrated problem. The effectiveness of the proposed approach is demonstrated in a representative case study. |
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| Keywords: | Virtual enterprise Partner selection Collaborative transportation scheduling Optimisation Genetic Algorithm |
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