AIMar 29, 2020

A hybrid optimization procedure for solving a tire curing scheduling problem

arXiv:2004.00425v1
Originality Synthesis-oriented
AI Analysis

This is an incremental improvement for tire manufacturing scheduling, addressing resource compatibility and demand timing.

The paper tackles a tire curing scheduling problem by developing a hybrid optimization procedure to minimize makespan while meeting demand, achieving optimal makespan for many instances, including large ones, by reducing model size.

This paper addresses a lot-sizing and scheduling problem variant arising from the study of the curing process of a tire factory. The aim is to find the minimum makespan needed for producing enough tires to meet the demand requirements on time, considering the availability and compatibility of different resources involved. To solve this problem, we suggest a hybrid approach that consists in first applying a heuristic to obtain an estimated value of the makespan and then solving a mathematical model to determine the minimum value. We note that the size of the model (number of variables and constraints) depends significantly on the estimated makespan. Extensive numerical experiments over different instances based on real data are presented to evaluate the effectiveness of the hybrid procedure proposed. From the results obtained we can note that the hybrid approach is able to achieve the optimal makespan for many of the instances, even large ones, since the results provided by the heuristic allow to reduce significantly the size of the mathematical model.

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