Fuzzifying approach to special cutting in poultry meat production planning

Abstract

ABSTRACT In this study, a method for assigning jobs in the special cutting of chicken parts was developed. In the developed method, a deterministic mathematical model is used to simulate the assignment of jobs in production lines for 1 week, with the maximum revenue from the weekly production employed as an objective function. Compared with human judgment for assigning jobs, the average weekly revenue increased by 27.9%, the average weekly throughput increased by 25.1%, and the average weekly backorders decreased by 13.4%. In addition, a fuzzy mathematical model was developed to assign jobs under uncertain demand and production time. In this model, the planner could select the membership level of two fuzzy parameters. The flexibility of demand and production time increased as the fuzzy parameters decreased. The mathematical model produced better results as the flexibility of the fuzzy parameters increased. The fuzzy mathematical model yielded better overall results compared to the deterministic model under realistic situations. Abbreviation: Deterministic mathematical model (DMM); Fuzzy mathematical model (FMM); Production planning (PP)