An efficient algorithm for stochastic capacity portfolio planning problems

Cheng Hung Wu, Ya Tang Chuang

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


This study investigates capacity portfolio planning problems under demand, price, and yield uncertainties. We model this capacity portfolio planning problem as a Markov decision process. In this research, we consider two types of capacity: dedicated and flexible capacity. Among these capacity types, flexible capacity costs higher but provides flexibility for producing different products. To maximize expected profit, decision makers have to choose the optimal capacity level and expansion timing for both capacity types. Since large stochastic optimization problems are intractable, a new heuristic search algorithm (HSA) is developed to reduce computational complexity. Compare to other algorithms in literature, HSA reduces computational time by at least 30% in large capacity optimization problems. In addition, HSA yields optimal solution in all numerical examples that we have examined.

Original languageEnglish
Pages (from-to)2161-2170
Number of pages10
JournalJournal of Intelligent Manufacturing
Issue number6
Publication statusPublished - 2012 Dec

All Science Journal Classification (ASJC) codes

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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