Abstract: The multiobjective evolutionary algorithm based on decomposition (MOEA/D) has received attention from researchers in recent years. This paper presents a new multiobjective algorithm based on decomposition and the cloud model called multiobjective decomposition evolutionary algorithm based on Cloud Particle Differential Evolution (MOEA/D-CPDE). In the proposed method, the best solution...

Multi-objective optimization problems arise frequently in applications but can often only be solved approximately by heuristic approaches. Evolutionary algorithms have been widely used to tackle multi-objective problems. These algorithms use different measures to ensure diversity in the objective space but are not guided by a formal notion of approximation. We present a new framework of an evol...

Since 1985 various evolutionary approaches to multiobjec-tive optimization have been developed, capable of searching for multiple solutions concurrently in a single run. But the few comparative studies of diierent methods available to date are mostly qualitative and restricted to two approaches. In this paper an extensive, quantitative comparison is presented, applying four multiobjective evolu...

Farm managers have to deal with many conflicting objectives when planning which crop to cultivate. Soil characteristics are extremely important when determining yield potential. Fertilization and liming are commonly used to adequate soils to the nutritional requirements of the crops to be cultivated. Planting the crop that will best fit the soil characteristics is an interesting alternative to ...

Bi-objective portfolio optimization for minimizing risk and maximizing expected return has received considerable attention using evolutionary algorithms. Although the problem is a quadratic programming (QP) problem, the practicalities of investment often make the decision variables discontinuous and introduce other complexities. In such circumstances, usual QP solution methodologies can not alw...

The loss of population diversity is one of the main problems in some applications of evolutionary algorithms. In order to maintain useful population diversity some special techniques must be used, like niching or co-evolutionary mechanisms. In this paper the mechanisms for maintaining population diversity in agent-based multi-objective (co-)evolutionary algorithms are proposed. The presentation...

This paper describes and evaluates a new noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective functions. This operator is designed with the Mann-Whitney U -test, which is a non-parametric (i.e., distribution-free) statistical significance test. It takes objective value samples of given two indiv...

a comprehensive and integrated study of any supply chain (sc) environment is a vital requirement that can create various advantages for the sc owners. this consideration causes productive managing of the sc through its whole wide components from upstream suppliers to downstream retailers and customers.  on this issue, despite many valuable studies reported in the current literature, considerabl...

A mobile ad-hoc network (MANET), a set of wirelessly connected sensor nodes, is a dynamic system that executes hop-by-hop routing independently with no external help of any infrastructure. Proper selection of cluster heads can increase the life time of the Ad-hoc network by decreasing the energy consumption. Although different methods have been successfully proposed by researchers to tackle...