Abstract
The Knapsack Problem with Setup (KPS) is a generalization of the classical Knapsack problem (KP), where items are divided into families. An individual item can be selected only if a setup is incurred for the family to which it belongs. This paper provides a dynamic programming (DP) algorithm for the KPS that produces optimal solutions in pseudo-polynomial time. In order to reduce the storage requirements of the algorithm, we adopt a new technique that consists in converting a KPS solution to an integer index. Computational experiments on randomly generated test problems show the efficiency of the DP algorithm compared to the ILOG's commercial product CPLEX 12.5. (C) 2015 Elsevier Ltd. All rights reserved.