In many real-world optimization applications there are often a number of conflicting objective functions that are all important to optimize. The purpose of multiobjective optimization (MOO) is to give the decision maker (DM) an understanding of how these functions are conflicting and the possibility to choose an appropriate trade-off between them. There are multiple methods for solving MOO prob...

Design of any complex system entails many objectives to reach and constraints to satisfy. This multi–objective nature of the problem ensures that the technology solution is always a compromise between conflicting objectives. The purpose of this paper is to demonstrate the application of Niched Pareto genetic algorithm as a relatively fast and straightforward method for obtaining technology sets...

Thermoacoustic heat engines (TAEs) are potentially advantageous drivers for thermoacoustic refrigerators (TARs). Connecting TAEs to TARs means that waste heat can effectively be utilized to provide cooling, and increase overall efficiency. However, this is currently a niche technology. Improvements can be made through a better understanding of the interactions of relevant design parameters. Thi...

In this paper, a hybrid method for solving multi-objective problem has been provided. The proposed method is combining the ε-Constraint and the Cuckoo algorithm. First the multi objective problem transfers into a single-objective problem using ε-Constraint, then the Cuckoo optimization algorithm will optimize the problem in each task. At last the optimized Pareto frontier will be drawn. The adv...

This article studies a class of multirobot coordination problems where team robots aim to reach their goal regions with minimum time and avoid collisions obstacles other robots. A novel numerical algorithm is proposed identify the Pareto optimal solutions no robot can unilaterally reduce its traveling without extending others'. The consistent approximation in epigraphical profile sense guarante...