it is shown in [1] that the optimal downlink radio resource allocation for non-realtime traffic in cellular cdma/tdma networks can be mapped to a multi-dimensional multiple-choice knapsack problem (mmkp) which is np-hard. in this correspondence we propose a heuristic algorithm with polynomial time complexity for this problem. numerical results indicate significant computational performance impr...

This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optim...

To further enhance the distribution uniformity and extensiveness of the solution sets and to ensure effective convergence of the solution sets to the Pareto front, we proposed a MOEA approach based on a clustering mechanism. We named this approach improved multi-objective evolutionary algorithm (LMOEA). This algorithm uses a clustering technology to compute and maintain the distribution and div...

This work proposes a load balance algorithm to parallel processing based on a variation of the classical knapsack problem. The problem considers the distribution of a set of partitions, defined by the number of clusters, over a set of processors attempting to achieve a minimal overall processing cost. The work is an optimization for the parallel fuzzy c-means (FCM) clustering analysis algorithm...

in this paper, a novel approach for multi response optimization is presented. in the proposed approach, response variables in treatments combination occur with a certain probability. moreover, we assume that each treatment has a network style. because of the probabilistic nature of treatment combination, the proposed approach can compute the efficiency of each treatment under the desirable reli...

The 0-1 knapsack problem is a well-known combinatorial optimisation problem. Approximation algorithms have been designed for solving it and they return provably good solutions within polynomial time. On the other hand, genetic algorithms are well suited for solving the knapsack problem and they find reasonably good solutions quickly. A naturally arising question is whether genetic algorithms ar...

The effect of different representations has been thoroughly analyzed for evolutionary algorithms in stationary environments. However, the role of representations in dynamic environments has been largely neglected so far. In this paper, we empirically compare and analyze three different representations on the basis of a dynamic multi-dimensional knapsack problem. Our results indicate that indire...

This paper deals with knapsack problem in fuzzy nature, where both the objective function and constraints are considered to be fuzzy. Three different models for proposed including, expected value model, chance-constrained dependent-chance model. Credibility ranking method is applied convert into a crisp equivalent linear one considering triangular trapezoidal numbers. The solution of obtained r...

In this paper, an interesting and easy method to solve the multi-dimensional  knapsack problem is presented. Although it belongs to the combinatorial optimization, but the proposed method belongs to the decision making field in mathematics. In order to, initially efficiency values for every item is calculated then items are ranked by using Multiple Criteria Decision Making (MCDA).  Finally, ite...

This paper considers online stochastic reservation problems, where requests come online and must be dynamically allocated to limited resources in order to maximize profit. Multi-knapsack problems with or without overbooking are examples of such online stochastic reservations. The paper studies how to adapt the online stochastic framework and the consensus and regret algorithms proposed earlier ...