A branch and bound algorithm for a single item nonconvex dynamic lot sizing problem with capacity constraints

A branch and bound algorithm for a single item nonconvex dynamic lot sizing problem with capacity constraints

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Article ID: iaor1989888
Country: United Kingdom
Volume: 17
Start Page Number: 199
End Page Number: 210
Publication Date: Jan 1990
Journal: Computers and Operations Research
Authors: ,
Keywords: optimization, programming: branch and bound
Abstract:

The authors develop a branch and bound algorithm for solving a deterministic single item nonconvex dynamic lot sizing problem with production and inventory capacity constraints. The production cost function is neither convex nor concave. It is a composite function with a fixed setup cost to start the production and a piecewise linear convex variable production cost. The algorithm finds a global optimum solution for the problem after solving a finite number of linear knapsack problems with bounded variables. Computational experience with randomly generated problems suggest that the algorithm solves the dynamic lot sizing problem in a computationally efficient manner both in terms of CPU time and storage requirements.

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