A review on aggregate production planning under uncertainty: Insights from a fuzzy programming perspective

Muhammad Qasim, Kuan Yew Wong, Komarudin

Research output: Contribution to journalArticlepeer-review

Abstract

It is essential to address uncertainties in different production planning strategies, notably aggregate production planning, which is a critical medium-term strategy. In this context, uncertainties typically appear as vagueness or impreciseness, leading to the prevalent adoption of fuzzy numbers to represent uncertain attributes. However, despite its significance, no dedicated study has exclusively examined aggregate production planning from the perspective of fuzzy mathematical programming. Thus, this review analyzed the published literature on fuzzy aggregate production planning and presented a classification scheme. In this review, various digital databases were explored, yielding a selection of 44 most relevant articles. Furthermore, this study thoroughly analyzed and reported various characteristics such as modelling and solution approaches, objective functions, fuzzy attributes, membership functions, aggregate operators, etc. The review revealed that fuzzy linear programming and fuzzy goal programming were the most utilized modelling approaches, with optimization solvers and metaheuristics standing out as the predominant solution approaches. Additionally, triangular fuzzy numbers emerged as the preferred method for the crisp formulation of fuzzy numbers. This review provides valuable insights into the existing research on fuzzy aggregate production planning and offers guidance to researchers to streamline their future research endeavors.

Original languageEnglish
Article number107436
JournalEngineering Applications of Artificial Intelligence
Volume128
DOIs
Publication statusPublished - Feb 2024

Keywords

  • Aggregate production planning
  • Fuzzy logic
  • Fuzzy mathematical programming
  • Impreciseness
  • Operational planning
  • Uncertainty
  • Vagueness

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