Scheduling Optimization in a Cloth Manufacturing Factory Using Genetic Algorithm with Fuzzy Logic for Multi-Objective Decisions

Abstract

The purpose of this work is the scheduling of trousers collection orders in the manufacturing factory of the development department of an important cloth manufacturing society in Tunisia. The scheduling of collection orders differ to the scheduling of production orders. These collections orders are small and average orders of various types of trousers for different international customers. From the anticipated customer information about the collection orders such us the anticipated dates of starting orders and exporting them, the quantities of each order and the combined importance of customer and style (fashion or classic style), we have studied the best orders scheduling solution which take in account all these information and constraints. We have for the first step studied the development department method for scheduling orders (classical method) which take in account only the priority rules either by anticipated beginning dates or by export dates. For a second step, we have used the fuzzy logic to include an importance factor to each order so that the scheduling problem becomes multi-objective. In the goal to optimisation of the result, we have used the genetic algorithm. The efficiency of this method was studied by comparing the fuzzy logic scheduling solution to the classical scheduling solution for the anticipated planning of the manufacturing factory.