We consider a task-operator-machine assignmentproblem where we seek to minimize the total execution time, to come as close as possible to a perfect load balance among the operators and not to exceed neither predefine...
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We consider a task-operator-machine assignmentproblem where we seek to minimize the total execution time, to come as close as possible to a perfect load balance among the operators and not to exceed neither predefined inter-operator communication costs nor a prefixed number of resources. Besides, in an industrial environment where work force frequently changes, manufacturing systems need to be flexible and critical decisions have to be quickly taken. In this context, a fuzzy genetic multiobjective optimization algorithm is developed to solve a multilevel generalized assignment problem usually encountered in the clothing industry.
Cutting planes have been used with great success for solving mixed integer programs. In recent decades, many contributions have led to successive improvements in branch-and-cut methods which incorporate cutting planes...
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Cutting planes have been used with great success for solving mixed integer programs. In recent decades, many contributions have led to successive improvements in branch-and-cut methods which incorporate cutting planes in branch and bound algorithm. Using advances that have taken place over the years on 0-1 knapsack problem, we investigate an efficient approach for 0-1 programs with knapsack constraints as local structure. Our approach is based on an efficient implementation of knapsack separation problem which consists of the four phases: preprocessing, row generation, controlling numerical errors and sequential lifting. This approach can be used independently to improve formulations with cutting planes generated or incorporated in branch and cut to solve a problem. We show that this approach allows us to efficiently solve large-scale instances of generalizedassignmentproblem, multilevel generalized assignment problem, capacitated -median problem and capacitated network location problem to optimality.
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