Solving Multi-Objective Manufacturing Problem with Demand Leakage, Uniform Fuzzy Demand and Sales

This paper focuses on a manufacturing system which produces a product in two grades – grade I and grade II. The manufacturing system under consideration also results into defective items which are further repaired and are sold in the secondary market. The price of grade I product is higher than that for grade II product because of the quality difference. The paper also considers demand leakage for the product of grade I which means that the some of the customers willing to pay for product of grade I, actually purchases product of grade II. The number of unsold units for both the grades of the product is sold at a giveaway price. Both the demand and sale are assumed to be fuzzy in nature. The purpose of this research study is to study the behavior of the system under demand leakage and other mentioned conditions. For this purpose, a three-objective problem has been proposed and Nondominated Sorting Genetic Algorithm – II (NSGA-II) has been applied to study the behavior of the proposed problem. The joint variations of all the objective values have been observed and analyzed. A numerical example shows the applicability of the proposed solution methodology.

[1]  W. Lieberman.  The Theory and Practice of Revenue Management , 2005 .

[2]  Li Yao,et al.  A newsvendor pricing game , 2004, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[3]  Moncer Hariga,et al.  Joint determination of target value and production run for a process with multiple markets , 2005 .

[4]  Syed Asif Raza,et al.  Joint determination of process mean, price differentiation, and production decisions with demand leakage: A multi-objective approach , 2016 .

[5]  Ali Gharbi,et al.  Production control of hybrid manufacturing–remanufacturing systems under demand and return variations , 2019 .

[6]  Peihuang Lou,et al.  Joint decision-making on automated disassembly system scheme selection and recovery route assignment using multi-objective meta-heuristic algorithm , 2019, Int. J. Prod. Res..

[7]  Michael Zhang,et al.  Optimal fences and joint price and inventory decisions in distinct markets with demand leakage , 2010, Eur. J. Oper. Res..

[8]  S. A. Raza.  An integrated approach to price differentiation and inventory decisions with demand leakage , 2015 .

[9]  Peter C. Bell,et al.  Price fencing in the practice of revenue management: An overview and taxonomy , 2012 .

[10]  Syed Asif Raza,et al.  Joint optimal determination of process mean, production quantity, pricing, and market segmentation with demand leakage , 2016, Eur. J. Oper. Res..

[11]  Angus Jeang.  Optimal determination of the process means, process tolerances, and resetting cycle for process planning under process shifting , 2009 .

[12]  Min Xie,et al.  Economic modelling for statistical process control subject to a general quality deterioration , 2016 .

[13]  M. A. Rahim,et al.  Integrated model for determining the optimal initial settings of the process mean and the optimal production run assuming quadratic loss functions , 2004 .

[14]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..