TY - JOUR
T1 - Multi-objective framework for process mean selection and price differentiation with leakage effects under price-dependent stochastic demand
AU - Raza, Syed Asif
AU - Abdullakutty, Faseela Chakkalakkal
AU - Rathinam, Sivakumar
AU - Govindaluri, Srikrishna Madhumohan
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2019/1
Y1 - 2019/1
N2 - This paper investigates the process mean selection problem that simultaneously considers pricing, production and quality decisions in a multi-objective context when the manufacturing firm experiences a demand leakage in simultaneously observed price-dependent stochastic demand. The output of the manufacturing process is segregated into two grades sold in primary and secondary markets using a differentiation price as the market segmentation tool. Nonconforming items are reworked at an additional cost and only price-dependent stochastic demand with leakage effects is assumed. Three objectives, expected gross income from sales, expected profit and expected product uniformity are considered in the proposed multi-objective optimization model. Two solution algorithms are proposed, a goal programming approach combined with a simulation based optimization and a multi-objective genetic algorithm. A detailed numerical experimentation is employed to compare the two algorithms.
AB - This paper investigates the process mean selection problem that simultaneously considers pricing, production and quality decisions in a multi-objective context when the manufacturing firm experiences a demand leakage in simultaneously observed price-dependent stochastic demand. The output of the manufacturing process is segregated into two grades sold in primary and secondary markets using a differentiation price as the market segmentation tool. Nonconforming items are reworked at an additional cost and only price-dependent stochastic demand with leakage effects is assumed. Three objectives, expected gross income from sales, expected profit and expected product uniformity are considered in the proposed multi-objective optimization model. Two solution algorithms are proposed, a goal programming approach combined with a simulation based optimization and a multi-objective genetic algorithm. A detailed numerical experimentation is employed to compare the two algorithms.
KW - Demand leakage
KW - Genetic algorithm
KW - Goal programming
KW - Multi-objective optimization
KW - Price differentiation
KW - Price-dependent stochastic demand
KW - Process mean
KW - Revenue management
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U2 - 10.1016/j.cie.2018.11.010
DO - 10.1016/j.cie.2018.11.010
M3 - Article
AN - SCOPUS:85056463555
SN - 0360-8352
VL - 127
SP - 698
EP - 708
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
ER -