This article addresses the problem of converting a single-objective combinatorial into multi-objective one using Pareto front approach. Although existing algorithms can identify optimal solution in space, they fail to satisfy constraints while achieving performance. To address this issue, we propose artificial bee colony optimization algorithm with classical theme called fitness sharing. approa...

In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...

Most of the existing dynamic multi-objective evolutionary algorithms (DMOEAs) are effective, which focuses on searching for approximation Pareto-optimal front (POF) with well-distributed in handling optimization problems (DMOPs). Nevertheless, real-world scenarios, decision maker (DM) may be only interested a portion corresponding POF (i.e., region interest) different instances, rather than who...

The Coati Optimization Algorithm (COA) has emerged as a prominent evolutionary algorithm renowned for its efficacy in addressing real-world problems. Its wide-ranging applicability across diverse domains is testament to exceptional performance and versatility. Compared other algorithms, COA been proven possess excellent global local search capabilities. This paper introduces novel self-organizi...

scheduling for job shop is very important in both fields of production management and combinatorial op-timization. however, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. the combination of several optimization criteria induces additional complexity and new problems. in this paper, we pro...

This paper presents a Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) for the optimal operation of a complex multipurpose and multi-reservoir system. Firstly, MOEA/D decomposes a multi-objective optimization problem into a number of scalar optimization sub-problems and optimizes them simultaneously. It uses information of its several neighboring sub-problems for optimizin...

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...

this paper presents a new hybrid method for optimal multi-objective reconfiguration in a distribution feeder in addition to determining the optimal size and location of multiple-distributed generation (dg). the purposes of this research are mitigation of losses, improving the voltage profile and equalizing the feeder load balancing in distribution systems. to reduce the search space, the improv...