1 Department of Commerce Automation and Management, National Pingtung University, Taiwan, R.O.C. 51 Min Sheng E. Road, Pingtung, 900, Taiwan
2 Department of Industrial Management, National Formosa University, Taiwan, R.O.C.
Cultural and creative commodities and services are not evaluated by the service provider, but by the users. According to the preliminary interviews, it is incorrect to assume that the more expensive, the more consumers like the products.
To analyze such commodities and services, this study employs a multi-objective planning model based on Value-Price-Cost theory to establish the relevant objectives and constraints.
A global search Particle Swarm Optimization (PSO) model is then established based on cluster analysis and grey theory. The three main operational mechanisms are: (1) an external repository to retain the optimal non-dominated solution set; (2) combined cluster analysis and grey theory to ensure a better distribution of the non-dominated solution search process; and (3) a virtual circle center, coupled with the existing positions of non-dominated solutions, to drive each particle of a multi-objective PSO (MOPSO) toward the optimal non-dominated solution.
The results of this research indicate that the proposed multi-objective algorithm outperforms both the conventional MOPSO and a non-dominated sorting genetic algorithm.
The managerial implication is that high commodity prices increase the total project cost and extend the completion time, but reduce the customer’s quality evaluation of the commodity.
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* Address correspondence to this author at the Department of Commerce Automation and Management, National Pingtung University, Taiwan, R.O.C., 51 Min Sheng E. Road, Pingtung, 900, Taiwan, R.O.C., Tel: 886-8-7663800, Fax: 886-8-7210801, E-mail: email@example.com