Hybrid mixed-integer/constraint logic programming strategies for solving scheduling and combinatorial optimization problems

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.