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...

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...

this paper presents the results of a comprehensive study on the efficiency of planar parallel mechanisms, considering their kinetostatic performance and also, their workspace. this aim is approached upon proceeding single- and multi-objective optimization procedures. kinetostatic performances of ten different planar parallel mechanisms are analyzed by resorting to a recent index, kinematic sens...