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Abstract
Multi-objective programming (MOP) is a branch of mathematical programming that has been widely used to deal with various practical problems. With the introduction of new technologies and business models, a paradigm shift in optimization problems is gradually taking place from fixed to flexible optimization. For example, many organizations use outsourcing or business process reengineering (BPR) to improve or upgrade their objective and technological coefficients to achieve better performance. Hence, traditional MOP models should be extended from the concept of fixed to changeable parameters, called changeable space, which includes decision space and objective space. In this paper, we propose three kinds of MOP model with changeable parameters to help decision-makers achieve the desired point (aspiration level), which is better than the ideal point.
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Notes on contributors
Jih-Jeng Huang
Jih-Jeng HUANG is an Associate Professor of Computer Science and Information Management at Soochow University, Taiwan, and teaches research method, multivariate analysis, and capital asset and pricing models, among others. He received his PhD in Information Management from the National Taiwan University. He has published on these interests widely in journals and conference proceedings. His current research interests include multiple criteria decision making, knowledge management, behavioural economics and finance, and data analysis.
Gwo-Hshiung Tzeng
Gwo-Hshiung TZENG is a Distinguished Chair Professor of National Taipei University, Taiwan. He received a Bachelor's degree in Business Management from the Tatung Institute of Technology (1967); a Master's degree in Urban Planning from Chung Hsing University (1971); and a PhD in Management Science from Osaka University, Japan (1977). He is Editor-In-Chief of the International Journal of Operations Research and the International Journal of Information Systems for Logistics and Management, among others. His current research interests include statistics, multivariate analysis, networks, routing and scheduling, multiple criteria decision making, fuzzy theory, hierarchical structure analysis for application to technology management, energy, environment, transportation systems, transportation investment, logistics, location, urban planning, tourism, technology management, electronic commerce, and global supply chains.
