Abstract
Aggregate production planning (APP) plays a critical role in supply chain management (SCM). This paper investigates multiproduct, multiperiod APP problems with several distinct types of fuzzy uncertainties. In contrast to the existing studies, the modelling in this work conserves the fuzziness such that the obtained APP is more effective. Based on Zadeh’s extension principle, the results obtained are fuzzy solutions described by membership functions, in contrast to results from previous studies. A pair of two-level parametric mathematical programs is formulated to calculate the lower and upper bounds of the optimum fuzzy performance measure. The membership function of the fuzzy total cost is constructed by enumerating various possibility levels. A case studied in previous research is investigated to demonstrate the validity of the proposed model and solution procedure. Because the optimal objective value and associated decision variables are expressed using fuzzy numbers rather than crisp values, the proposed approach is able to represent APP systems more accurately, and therefore, the results obtained can provide decision makers with more effective and informative APPs and more chance to achieve the optimal disaggregate plan.
Highlights
Current trends in the highly competitive and dynamic business environment are driving companies across the globe to move towards aggregate production planning (APP) with the intent of finding optimum balance among capacity, forecasted demand, and fluctuating customer orders over the midterm, often from 3 to 18 months ahead
The fuzzy APP model is transformed into a family of crisp APP models that are described by a pair of mathematical programs
This approach allows the users to derive the membership function of the fuzzy minimum total costs of the APP problem associated with the fuzzy parameters
Summary
Current trends in the highly competitive and dynamic business environment are driving companies across the globe to move towards aggregate production planning (APP) with the intent of finding optimum balance among capacity, forecasted demand, and fluctuating customer orders over the midterm, often from 3 to 18 months ahead. Chen and Huang [37] proposed a solution procedure that is able to find the fuzzy objective value of the fuzzy APP model They only investigated the single-product APP problem with two sets of fuzzy parameters, the maximum workforce available and the forecasted demand. This paper proposes a cost-based multiproduct/ multiperiod APP model with several sets of fuzzy parameters, including the unit production costs excluding labour costs, overtime labour costs, labour costs, inventory carrying costs, costs to hire one worker, costs to lay off one worker, unit backorder costs, conversion factors in hours of labour, forecasted demands, and maximum workforce.
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