An integrated optimization algorithm of GA and ACA-based approaches for modeling virtual enterprise partner selection

Abstract

In the emerging information age, traditional enterprises have been increasingly replaced by virtual enterprises because they are incompatible with new business environments. The virtual enterprise, also called the dynamic alliance, gradually becomes a new organization pattern. In the process of establishing virtual enterprises, the appropriate method of partner selection is one of key problems. After reviewing the virtual enterprise concept, characteristics, and constitution, this paper proposes a hybrid algorithm in which it fuses the Genetic Algorithm (GA) into an Ant Colony Optimization Algorithm (ACA) for optimizing the problem of partner selection. The paper briefly analyzes some flaws and merits in both ACA and GA methods and proposes the benefits and necessity of applying the integration of GA into ACA to resolve partner selection problems. A hybrid algorithm is then presented for optimizing the problem of virtual enterprise partner selection. Finally, the result of an illustrative numerical case demonstrates the integrated algorithm, showing better performance in both efficiency and effectiveness than the GA and ACA methods in partner selection. The conclusions in this paper can be useful for guiding problem solving in similar virtual enterprise scenarios.

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