Emergence of chip multiprocessor systems has dramatically increased the performance potential of computer systems. Since the amount of exploited parallelism is directly influenced by the selection of the algorithm, algorithmic choice also plays a critical role in achieving high performance on modern architectures. Hence, in the era of multicore computing, it is important to re-evaluate algorith...

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 ...

This paper deals with three particular models of the bi-criteria {0,1}-knapsack problem: equal weighted items, constant sum of the criteria coe¢cients, and the combination of the two previous models. The con...guration of the Pareto frontier is presented and studied. Several properties on the number and the composition of the e¢cient solutions are devised. The connectedness of the e¢cient solut...

Constraint Programming (CP) is a very general programming paradigm that proved its efficiency on solving complex industrial problems. Most real-life problems are stochastic in nature, which is usually taken into account through different compromises, such as applying a deterministic algorithm to the average values of the input, or performing multiple runs of simulation. Our goal in this paper i...