Abstract
This paper addresses the irregular strip packing problem, a particular two-dimensional cutting and packing problem in which convex/nonconvex shapes (polygons) have to be packed onto a single rectangular object. We propose an approach that prescribes the integration of a metaheuristic engine (i.e., genetic algorithm) and a placement rule (i.e., greedy bottom-left). Moreover, a shrinking algorithm is encapsulated into the metaheuristic engine to improve good quality solutions. To accomplish this task, we propose a no-fit polygon based heuristic that shifts polygons closer to each other. Computational experiments performed on standard benchmark problems, as well as practical case studies developed in the ambit of a large textile industry, are also reported and discussed here in order to testify the potentialities of proposed approach.
Highlights
The constant competitiveness between the modern industries requires that a part of the investments has to be directed to the optimization of the production processes
We propose a novel approach based on the aggregation between a modified genetic algorithm and a greedy bottom-left procedure for tackling the target problem [6, 7]
The main objective is to minimize the length of the layouts, while the width remains fixed
Summary
The constant competitiveness between the modern industries requires that a part of the investments has to be directed to the optimization of the production processes. Glass, paper, sheet metal, textile, and wood industries, for instance, the main concern is to avoid the excessive expenditure of raw material required to meet a particular demand. In this scenario, the two-dimensional irregular strip packing problem is included. The irregular strip packing problem is known to be NPhard even without rotation [5], meaning that its globally optimal solution is unlikely to be found by polynomialtime algorithms.
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