Production sequencing in a flow shop system using optimization and heuristic algorithms
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Caicedo-Rolón, Alvaro Jr | 2021-03-31
The purpose of the research was to determine the sequencing of the production of n
jobs in m operations in a small footwear company in an environment of flow shop machine
characteristics, which optimizes the total time of completion of the job in the production system
(Makespan). We used heuristic algorithms that were applied through Lekin and WinQSB
softwares, and for the optimization algorithm we designed a mathematical model that was solved
by Juliabox software. Results show that the integer linear programming and local search minimize
the makespan with 3807 minutes, and different production sequences for each algorithm, which
consider permutation, which improves the traditional way of programming the production in 97
minutes, however, the optimization presents better results in the performance measures of
average waiting time, average time of flow, and average job in process. Application of heuristic
algorithms proves to be simple and fast, but the mathematical model of optimization designed
and encoded in the software is a flexible and valuable tool for decision making in production
programming, which could be applied in other footwear companies, and in other productive
sectors whose companies have the same characteristics of the case study, reducing costs and
improving delivery times.
LEER