Journal
COMPUTERS & CHEMICAL ENGINEERING
Volume 24, Issue 2-7, Pages 337-343Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0098-1354(00)00470-1
Keywords
mixed integer programming; constraint logic programming; hybrid MIP/CLP
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In this paper, we present two methods to overcome the combinatorial complexity when solving large discrete optimization problems. The basic idea relies on combining mixed integer programming (MIP) and constraint logic programming (CLP) to exploit their complementary strengths. These strategies are illustrated in the area of job-shop scheduling and trim-loss problems. Comparisons of the strategies are presented with direct solutions on MIP and CLP problems. (C) 2000 Elsevier Science Ltd. All rights reserved.
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