This paper presents a state-of-the-art review on multi-objective metaheuristics for multi-
objective discrete optimization problems (MODOPs). The relevant literature source and their …

Although the community of nature-inspired computing has witnessed a wide variety of
metaheuristics, it often requires considerable effort to adapt them to different combinatorial …

This paper presents an efficient cooperative multi-populations swarm intelligence algorithm
based on the Harris Hawks optimization (HHO) algorithm, named CMPMO-HHO, to solve …

The ongoing container shortage crisis has presented significant challenges for the freight
forwarding industry, requiring companies to implement adaptive measures in order to …

Many real-world optimization problems require optimizing multiple conflicting objectives
simultaneously, and such problems are called multiobjective optimization problems (MOPs) …

Finding a good compromise between intensification and diversification mechanisms is very
challenging task when solving multi-objective optimization problems (MOPs). In this paper …

Despite the good performance of Crow Search Algorithm (CSA) in dealing with global
optimization problems, unfortunately it is not the case with respect to the convergence …

In this paper, we propose a parallel multiobjective evolutionary algorithm called Parallel
Criterion-based Partitioning MOEA (PCPMOEA), with an application to the Multiobjective …

This paper shows that the many greedy strategies that have been designed to repair
infeasible solutions to multi-objective knapsack problems (MOKPs) with small item …

Penetration of electrical vehicles and distributed generation resources in distribution
networks is increasing, and it is needed to investigate their effect on system′ s operation …