A retailer inventory model when the reliability of inspection system affects the percentage of defective items which are delivered to final customers

ABSTRACT

This paper studies an inventory model system in which the inspection system reliability hinges on the reliability of its components and affects recognition of defective items over the planning horizon. The inventory model is discussed during the useful life of the inspection system and its components will be sold at the end of the useful life at the price of salvage value. The goal is choosing the internal components of the inspection system, determining the order and fixed shortage quantity, number of ordering cycles to maximize the revenue that is gained by the retailer. After that the model is formulated and discussed in details, particle swarm optimization (PSO) and genetic algorithm (GA) are used to solve the proposed model. To demonstrate the application of the proposed methodology and assessing the performances of the solution algorithms, different numerical examples are solved and compared.

KEYWORDS:

• Probabilistic inventory models
• reliability
• exponential distribution
• inspection system
• shortage

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Behzad Maleki Vishkaei

Behzad Maleki Vishkaei received his BS and MS degrees in Industrial Engineering from Islamic Azad University, Qazvin, Iran. He is currently a PhD candidate in the industrial Engineering Department at Mazandaran University of Science & Technology. His research interests include areas of Inventory Control, Supply Chain Management, Reliability and Data Mining.

Mehdi Seyyed-Esfahani

Mehdi Seyyed-Esfahani is a professor of Industrial Engineering at Amirkabir University of Technology. He received his BSc from Sharif University of Technology and his MSc and PhD from Bradford University. He is a member of editorial board in several domestic journals and also has more than 50 research papers in high‐ranked international and domestic journals, such as European Journal of Operations Research, International Journal of Advanced Manufacturing Technology, Expert Systems with Applications, and International Journal of Systems Science. His primary research interests include reliability theory and applications, statistical quality control, quality management, operations management, and supply chain management. Also, More than 30 PhD theses and 200 MSc dissertations have been published under his supervision.

Iraj Mahdavi

Iraj Mahdavi is the distinguished Professor of Industrial Engineering at Mazandaran University of Science and Technology and Vice President of Graduate Studies and Research. He received his PhD from India in Production Engineering and Post-Doctorate professor from Hanyang University, Korea. He is also in the editorial board of five journals. He has published over 200 research papers. His research interests include Cellular Manufacturing, Digital Management of Industrial Enterprises, Intelligent Operation Management and Industrial Strategy Setting.

Masoud Askari

Masoud Askari received his BS degree in Industrial Engineering from Hormozgan University, Hormozgan, Iran and MS degree in Industrial Engineering from Shahid Bahonar University, Kerman, Iran. He is currently a PhD candidate in the industrial Engineering Department at Mazandaran University of Science & Technology. His research interests include areas of Inventory Control, Supply Chain Management, Data Mining and Big Data.