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Heuristics and reduction methods for multiple constraints 0-1 linear programming problems. (English) Zbl 0579.90066
Summary: This work extends the efficient results relative to the 0-1 knapsack problem to the multiple inequality constraints 0-1 linear programming problems. The two crucial phases for the solution of this type of problems are presented: (i) Two linear expected time complexity greedy algorithms are proposed for the determination of a lower bound on the optimal value by using a cascade of surrogate relaxations of the original problem whose sizes are decreasing step by step. A comparative study with the best known heuristic methods is reported; it concerned the accuracy of the approximate solutions and the practical computational times. (ii) This greedy algorithm is inserted in an efficient reduction framework. Variables and constraints are eliminated by the conjunction of tests applied to Lagrangean and surrogate relaxations of the original problem. A lot of computational results are summarized by considering test problems of the literature.

MSC:
90C09 Boolean programming
65K05 Numerical mathematical programming methods
90C05 Linear programming
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