New product introduction planning using a 0–1 semi-infinite programming model

Abstract

A quantitative approach to screen products to the market was proposed. Product life cycles describe the whole process from new products introduction through trial production to the point when it is phased out. In theory, product life cycles go though four stages including introduction, growth, maturity and decline. However, there are very few practical products following such a prescriptive cycle. Based on product family analysis, the characteristics of new products can be classed into four categories with respective benefit curves and parameters. The curve parameters of each type can be determined according to the data derived from market prediction. A 0–1 semi-infinite programming (0–1 SIP) model was presented to describe the problem of new products introduction. An inexact approach to 0–1 semi-infinite programming was recommended for the model solution. Examples with numerical results indicate the potential industrial applications of the proposed approach.

Keywords:

• New product introduction planning
• Product life cycles
• Profit curves
• 0–1 semi-infinite programming
• Optimization

Acknowledgements

This research was partly supported by the National High-tech Program (No. 863-511-9844-011) and the National Natural Science Foundation (No. 69974039) of PR China, and partly by the Competitive Earmarked Research Grant of Hong Kong (CERG Project No. 9040420).

Fucai Wan was born in Heilongjiang, China. He received his PhD degree in Systems Engineering from Northeastern University, Shenyang, China. He has been a Postdoctoral Fellow at Dalian University of Technology, Dalian, China. He is now an Associate Professor in the College of Information Engineering, Shenyang University, China. His current scope of teaching and research covers computer applications, product life cycle management, new product development, modelling and optimization and evolutionary computation. He has co-authored two books and more than 10 papers published in international and domestic journals.

Dingwei Wang was born in Nanjing, China. He received his PhD degree in Control Theory and Applications from Northeastern University, Shenyang, China. He has been a Postdoctoral Fellow at North Carolina State University, Raleigh, USA. He is currently a Professor and Director with the Institute of Systems Engineering, College of Information Science and Engineering, Northeastern University, China. He serves on the editorial board of Fuzzy Optimization and Decision Making. He has authored and co-authored five books and more than 200 papers published in international and domestic journals. His current research interests include production planning and scheduling, modelling and optimization, evolutionary computation and artificial life.

Richard Y. K. Fung obtained a BSc (Hons) in Production Engineering and a Master of Philosophy (MPhil) degree in Manufacturing Resource Planning, both from Aston University in Birmingham, UK. Subsequently, he was awarded a PhD degree in Customer Requirements Management by Loughborough University, UK. He has worked in the industry for over 12 years, having been involved in different manufacturing areas including product development, production planning and control, design and implementation of management information systems, and management consultancy in UK. Dr Fung joined the City University of Hong Kong in 1989, and he is now an Associate Professor and Director of the Laboratory of Enterprise Knowledge Integration and Transfer in the Department of Manufacturing Engineering and Engineering Management. His current scope of teaching and research covers knowledge management, quality management, customer requirements analysis, quality function deployment, supply-chain management, product life cycles management, and the applications of artificial intelligence techniques in the industry.