Iterated Tabu Search for the Unconstrained Binary Quadratic Optimization Problem

Given a set of objects with profits (any, even negative, numbers) assigned not only to separate objects but also to pairs of them, the unconstrained binary quadratic optimization problem consists in finding a subset of objects for which the overall profit is maximized. In this paper, an iterated tabu search algorithm for solving this problem is proposed. Computational results for problem instances of size up to 7000 variables (objects) are reported and comparisons with other up-to-date heuristic methods are provided. Key words: binary quadratic optimization, iterated tabu search, heuristics.

• Type: Journal
• Year: 2006
• Where: INFORMATICALT
• Authors: Gintaras Palubeckis
• Keywords: Binary Quadratic Optimization, INFORMATICALT 2006, Quadratic Optimization Problem, Tabu Search