| dc.description.abstract | The aim of the study is to investigate the aggregate production planning (APP) problem
with fuzzy stochastic demand. A novel fuzzy interval representation, Gaussian process,
and chance-constraint programing are employed to transform the fuzzy stochastic APP
problem into an equivalent Mixed Integer Linear Programming (MILP) model.
Matheuristics are proposed as the solution approach, utilizing a Genetic Algorithm for
the single-objective problem and the Non-Dominated Sorting Genetic Algorithm II
(NSGA-II) for the multi-objective problem. Large-scale computational experiments
have also been conducted to demonstrate that the proposed method not only yields
promising results to both single and multi-objective MILP approaches but also
significantly reduces computation time. In real life application, a case study of ABC
company is also employed to show the effectiveness of the proposed approach. | en_US |
