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 Govindaluri

Research output: Contribution to journalArticle

2 Citations (Scopus)


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
JournalComputers and Industrial Engineering
Publication statusAccepted/In press - Jan 1 2018



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

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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