Most of the complex research problems can be formulated as optimization problems.
Emergence of big data technologies have also commenced the generation of complex …

Swarm intelligence is a kind of artificial intelligence that is based on the collective behavior
of the decentralized and self-organized systems. This work focuses on reviewing a heuristic …

This article proposes an adaptive localized decision variable analysis approach under the
decomposition-based framework to solve the large-scale multiobjective and many-objective …

There exist many multiobjective optimization problems (MOPs) containing a large number of
decision variables in real-world applications, which are known as large-scale MOPs. Due to …

Solving multiobjective optimization problems (MOPs) through metaheuristic methods gets
considerable attention. Based on the classical variation operators, several enhanced …

To solve the hybrid flow-shop scheduling problem in sand casting enterprises with
multivariate and multistage production characteristics, an improved cuckoo algorithm was …

In this work, we explore a novel multi-objective optimization algorithm to identify a set of
solutions that could be optimal for more than one task. The proposed approach is used to …

Industrial systems usually draw huge energy to run various machines. The amount of energy
requirement has again increased due to the automation of the industrial plants to make them …

This study investigates a new two-machine flow shop group scheduling problem with job-
related blocking and transportation times, which is derived from the realistic pipe-making …

Multi-core systems are any computing device nowadays and stream processing applications
are becoming recurrent workloads, demanding parallelism to achieve the desired quality of …