TY - JOUR
T1 - A review on aggregate production planning under uncertainty
T2 - Insights from a fuzzy programming perspective
AU - Qasim, Muhammad
AU - Wong, Kuan Yew
AU - Komarudin,
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2024/2
Y1 - 2024/2
N2 - 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.
AB - 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.
KW - Aggregate production planning
KW - Fuzzy logic
KW - Fuzzy mathematical programming
KW - Impreciseness
KW - Operational planning
KW - Uncertainty
KW - Vagueness
UR - http://www.scopus.com/inward/record.url?scp=85181586907&partnerID=8YFLogxK
U2 - 10.1016/j.engappai.2023.107436
DO - 10.1016/j.engappai.2023.107436
M3 - Article
AN - SCOPUS:85181586907
SN - 0952-1976
VL - 128
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
M1 - 107436
ER -