This paper deals with the problem of optimizing a linear function over efficient set 0-1 bi-objective knapsack problem. Such represents main criterion posed. The resolution process is based essentially on dynamic programming. proposed method provides subset solutions including one which optimizes without having to enumerate all Numerical experiments are reported, different instances large sizes...

An employee transporting problem is described and a set partitioning model is developed. An investigation of the model leads to a knapsack problem as a surrogate problem. Finding a partition corresponding to the knapsack problem provides a solution to the problem. An exact algorithm is proposed to obtain a partition (subset-vehicle combination) corresponding to the knapsack solution. It require...

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...

In this paper a hybrid parallel multi-objective genetic algorithm is proposed for solving 0/1 knapsack problem. Multi-objective problems with non-convex and discrete Pareto front can take enormous computation time to converge to the true Pareto front. Hence, the classical multi-objective genetic algorithms (MOGAs) (i.e., non-Parallel MOGAs) may fail to solve such intractable problem in a reason...

one main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. this paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. indeed, the nature of products is considered different and hub capacity constraint is also applied. due to ...

The stochastic knapsack problem is a natural generalization of classical knapsack problem. In this problem, we are given a set of items each associated with a probability distribution on sizes and a profit, and a knapsack of unit capacity. The size of an item is unknown before inserting it into the knapsack, and it is revealed as soon as the item inserted into the knapsack. The objective is to ...

an integrated model considers all parameters and elements of different deficiencies in one problem. this paper presents a new integrated model of a supply chain that simultaneously considers facility location, vehicle routing and inventory control problems as well as their interactions in one problem, called location-routing-inventory (lri) problem. this model also considers stochastic demands ...

This paper proposes an improved version of volume dominance to assign fitness to solutions in Pareto-based multi-objective optimisation. The impact of this revised volume dominance on the performance of multi-objective evolutionary algorithms is investigated by incorporating it into three approaches, namely SEAMO2, SPEA2 and NSGA2 to solve instances of the 2-, 3and 4objective knapsack problem. ...