The multi-objective optimization (MOO) of complex systems remains a challenging task in engineering domains. methodological approach applying MOO algorithms to simulation-enabled models has established itself as standard. Despite increasing computational power, the effectiveness and efficiency such algorithms, i.e., their ability identify many Pareto-optimal solutions possible with few simulati...

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 ...

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...