Competitive Decision Algorithm for Multidimensional Knapsack Problem

The multidimensional knapsack problem (MKP) is a classified NP-hard optimization problem, which is a generalisation of the 0-1 simple knapsack problem(KP). It consists in selecting a subset of given items in such a way that the total profit of the selected items is maximized while a set of knapsack constraints are satisfied. The NW is resource allocation model that is one of the most well-known integer programming problems. It often appears in decision making and programming, resource distribution, loading, and so on. For solving this problem, many algorithms such as simulated annealing, genetic algorithm, ant colony algorithm, and other heuristic algorithms have been proposed by scholars. Based on some properties of multidimensional knapsack problem, a competitive decision algorithm(CDA) for MKP is proposed. Competitive decision algorithm is a new optimization algorithm based on the analysis of the mechanism of natural competitions and the principle of decision. It uses the characteristics that competition builds optimization and the result of competition hinges on decision. We use this algorithm to solve many test instances of multidimensional knapsack problems and computational result results in good performances.