A soft approach for hard continuous optimization |
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| Affiliation: | 1. Department of Management Information Science, Chiba Institute of Technology, Chiba 275-0016, Japan;2. School of Administrative Studies, York University, 4700 Keele Street, Toronto, Canada M3J 1P3;1. Department of Finance, Autonomous University of Madrid, Ciudad Universitaria De Cantoblanco 28049 Madrid, Spain;2. Department of civil Engineering, Polytechnic University of Cartagena, Ctra. De la Fuensanta, 19, Bajo B, 30012 Murcia, Spain;1. Division of Roads and Bridges, Faculty of Civil Engineering, Opole University of Technology, Katowicka street 48, 45-061 Opole, Poland;2. Department of Civil Engineering and Architecture, Faculty of Civil Engineering, Opole University of Technology, Katowicka street 48, 45-061 Opole, Poland;1. Dipartimento di Economia, Management e Diritto d''Impresa, Università degli Studi di Bari, Italy;2. Dipartimento di Economia, Università degli Studi di Foggia, Italy |
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| Abstract: | This paper is to introduce a soft approach for solving continuous optimizations models where seeking an optimal solution is theoretically or practically impossible.We first review methods for solving continuous optimization models, and argue that only a few optimization models with some good structure are solved. To solve a larger class of optimization problems, we suggest a soft approach by softening the goal in solving a model, and propose a two-stage process for implementing the soft approach. Furthermore, we offer an algorithm for solving optimization models with a convex feasible set, and verify the validity of the soft approach with numerical experiments. |
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