A forward-looking matheuristic approach for the multi-period two-dimensional non-guillotine cutting stock problem with usable leftovers

TL;DR

This paper introduces a forward-looking matheuristic for the multi-period 2D non-guillotine cutting stock problem with leftovers, optimizing costs and leftover value over time.

Contribution

It presents a novel forward-looking matheuristic that considers future impacts of current decisions in multi-period cutting stock problems.

Findings

The approach outperforms myopic methods in numerical tests.

It effectively estimates leftover utilization to improve decision-making.

The method reduces overall costs while increasing leftover value.

Abstract

In [E. G. Birgin, O. C. Rom\~ao, and D. P. Ronconi, The multi-period two-dimensional non-guillotine cutting stock problem with usable leftovers, International Transactions in Operational Research 27(3), 1392-1418, 2020] the multi-period two-dimensional non-guillotine cutting stock problem with usable leftovers was introduced. At each decision instant, the problem consists in determining a cutting pattern for a set of ordered items using a set of objects that can be purchased or can be leftovers of previous periods; the goal being the minimization of the overall cost of the objects up to the considered time horizon. Among solutions with minimum cost, a solution that maximizes the value of the leftovers at the end of the considered horizon is sought. A forward-looking matheuristic approach that applies to this problem is introduced in the present work. At each decision instant, the objects and the cutting pattern that will be used is determined, taking into account the impact of this decision in future states of the system. More specifically, for each potentially used object, an attempt is made to estimate the utilization rate of its leftovers and thereby determine whether the object should be used or not. The approach's performance is compared to the performance of a myopic technique. Numerical experiments show the efficacy of the proposed approach.