Multi-objective framework for process mean selection and price differentiation with leakage effects under price-dependent stochastic demand

Syed Asif Raza*, Faseela Chakkalakkal Abdullakutty, Sivakumar Rathinam, Srikrishna Madhumohan Govindaluri

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)698-708
Number of pages11
JournalComputers and Industrial Engineering
Volume127
DOIs
Publication statusPublished - Jan 2019

Keywords

  • Demand leakage
  • Genetic algorithm
  • Goal programming
  • Multi-objective optimization
  • Price differentiation
  • Price-dependent stochastic demand
  • Process mean
  • Revenue management

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering

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