期刊
COMPUTERS & CHEMICAL ENGINEERING
卷 44, 期 -, 页码 84-93出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2012.04.015
关键词
Mixed integer linear programming; Feasibility cut; Dinkelbach's method; Scheduling; Fractional programming; CPLEX
资金
- Ministry of Knowledge Economy (MKE, Korea) [10038671]
- NSERC
- University of Alberta
- Korea Evaluation Institute of Industrial Technology (KEIT) [10038671] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This paper presents a novel strategy for speeding up the classical Benders decomposition for large-scale mixed integer linear programming problems. The proposed method is particularly useful when the optimality cut is difficult to obtain. A ratio of distances from a feasible point to an infeasible point and a feasibility cut is used as a metric to determine the tightest constraint for the region located by the feasible point, thus improving the convergence rate. Application of the proposed approach to a multi-product batch plant scheduling problem shows substantial improvement both in the computational time and the number of iterations. (C) 2012 Elsevier Ltd. All rights reserved.
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