The multidimensional multi-choice knapsack problem (MMKP) is one of the most complex members of the Knapsack Problem (KP) family. It has been used to model large problems such as telecommunications, quality of service (QoS), management problem in computer networks and admission control problem in the adaptive multimedia systems. In this paper, we propose a new approach based on strategic oscill...

We describe a tabu search (TS) approach for solving general zero-one mixed integer programming (MIP) problems that exploits the extreme point property of zero-one solutions. Specialized choice rules and aspiration criteria are identified for the problems, expressed as functions of integer infeasibility measures and objective function values. The first-level TS mechanisms are then extended with ...

25 CRITICAL EVENT TABU SEARCH FOR MULTIDIMENSIONAL KNAPSACK PROBLEMS Fred Glover Graduate School of Business, Box 419 University of Colorado at Boulder Boulder, Colorado, 80309-0419 E-Mail: [email protected] Gary A. Kochenberger College of Business University of Colorado at Denver Denver, Colorado 80217-3364 E-Mail: [email protected] We report a new approach to creating a ...

In the classical deterministic knapsack problem, a knapsack of capacity C is given, together with K classes of objects. For every k = 1, . . . ,K, each object of the class k has a size bk and an associated reward rk. The objects can be placed into the knapsack as long as the sum of their sizes does not exceed the capacity C. The problem consists in placing the objects inside the knapsack so as ...

Multiple Knapsack Problem (MKP) is a most popular multiple subset selection problem that belongs to the class of NP-Complete problems. The aim is to assign optimal subsets among all original items to some knapsacks, such that the overall profit of all selected items be maximised, while the total weight of all assigned items to any knapsack does not exceed the allowable capacity of it. Artificia...

This paper presents a layered encoding cascade evolutionary approach to solve a 0/1 knapsack optimization problem. A layered encoding structure is proposed and developed based on the schema theorem and the concepts of cascade correlation and multi-population evolutionary algorithms. Genetic algorithm (GA) and particle swarm optimization (PSO) are combined with the proposed layered encoding stru...

The mean field theory approach to knapsack problems is extended to multiple knapsacks and generalized assignment problems with Potts mean field equations governing the dynamics. Numerical tests against "state of the art" conventional algorithms shows good performance for the mean field approach. The inherently parallelism of the mean field equations makes them suitable for direct implementation...

One of the combinatorial optimization problems is Knapsack problem, which aims to maximize benefit objects whose weight not exceeding capacity knapsack. This paper introduces artificial bee colony algorithm select a subset project and represented by knapsack problem put best investment plan achieve highest profits within determined costs, this one applications financial field. The result from p...

Real-life planning problems are often complicated by the occurrence of disturbances, which imply that the original plan cannot be followed anymore and some recovery action must be taken to cope with the disturbance. In such a situation it is worthwhile to arm yourself against common disturbances. Well-known approaches to create plans that take possible, common disturbances into account are robu...

This paper deals with the problem of inaccuracy of the solutions generated by metaheuristic approaches for bi-criteria {0,1}-knapsack problems. A hybrid approach which combines systematic and heuristic search is proposed to reduce that inaccuracy in the context of a scatter search method. The components of the method are used to determine regions in the decision space to be systematically searc...