Meta-heuristic Optimization Techniques

Applications in Engineering

Anuj Kumar, Sangeeta Pant, Mangey Ram, Om Yadav, Anuj Kumar, Sangeeta Pant, Mangey Ram, Om Yadav

• Éditeur: De Gruyter
• Année: 2022
• ISBN:
  9783110716252
• Édition: 1
• Sujet: Informatique
• Sous-sujet: Réseaux de neurones

This book offers a thorough overview of the most popular and researched meta-heuristic optimization techniques and nature-inspired algorithms. Their wide applicability makes them a hot research topic and an effi cient tool for the solution of complex optimization problems in various fi elds of sciences, engineering, and in numerous industries.

Application of particle swarm optimization technique in an interval-valued EPQ model

Subhendu Ruidas

Department of Mathematics, Sonamukhi College, Bankura, India

Mijanur Rahaman Seikh

Department of Mathematics, Kazi Nazrul University, Asansol, India

Prasun Kumar Nayak

Department of Mathematics, Midnapore College (Autonomous), Midnapore, India

Abstract

There are certain practical scenarios in the field of engineering, science, and management where the derivative-based methods or the gradient-based iterative methods for optimization fail because of the highly complex nature of the problem. The application of some heuristic or meta-heuristic search algorithms becomes fruitful in those scenarios to obtain the optimum solution. particle swarm optimization (PSO) technique is one such algorithm based on the hunting technique of a flock of beasts in the jungle. In this chapter, an economic production quantity (EPQ) model is developed under an imperfect production system allowing shortages. In reality, the screening procedure for finding out the defective items may not be 100% perfect. As a result, some faulty products may be counted as good products and may reach the customer resulting in a sales return. On the other hand, most of the existing EPQ models consider...