Given the increasing public awareness of environmental impacts, governments have made regulation on pollutants more stringent. Therefore, the Unit Commitment Problem (UCP), which traditionally minimizes the total production costs, needs to consider the pollutants emissions as another objective. This way, the UCP becomes a multiobjective problem with two competing objectives. The approach propos...

In the field of optimization computation, there has been a growing interest in applying intelligent algorithms to solve multi-objective optimization problems (MOPs). This paper focuses mainly on the multiobjective evolutionary algorithm based on decomposition, MOEA/D for short, which offers a practical general algorithmic framework of evolutionary multi-objective optimization, and has been achi...

Tests of crude oil toxicity to fish are often chronic, exposing embryos from fertilization to hatch to oil solutions prepared using standard mixing procedures. However, during oil spills, fish are not often exposed for long periods and the dynamic nature of the ocean is not easily replicated in the lab. Our objective was to determine if brief exposures of Atlantic herring (Clupea harengus) embr...

Abstract. Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algor...

Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(mN3) computational complexity (where m is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algo...

This research uses a comprehensive method to solve a combinatorial problem of distribution network expansion planning (DNEP) problem. The proposed multi-objective scheme aims to improve power system's accountability and system performance parameters, simultaneously, in the lowest possible costs. The dynamic programming approach is implemented in order to find the optimal sizing, siting and timi...

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-...