Reactive GRASP for the strip-packing problem

Abstract

This paper presents a greedy randomized adaptive search procedure (GRASP) for the strip packing problem, which is the problem of placing a set of rectangular pieces into a strip of a given width and infinite length so as to minimize the required length. We investigate several strategies for the constructive and improvement phases and several choices for critical search parameters. We perform extensive computational experiments with wellknown instances which have been previously reported, first to select the best alternatives and then to compare the efficiency of our algorithm with other procedures. The results show that the GRASP algorithm outperforms recently reported metaheuristics.

A Tabu Search Algorithm with Direct Representation for Strip Packing

“…2 with the previously reported TS algorithms denoted as "TS1" [13] and "TS2" [12] and the best performing approaches: GRASP [6] and IDW [7]. Note that TS was also tried in [8], achieving "good performance", but no numerical results were reported.…”

“…Exact algorithms have also been considered but they are usually limited to "small instances" (up to 200 objects) [22,23,24,25]. Among these procedures, the approximate GRASP and IDW approaches [6,7] are probably the best performing ones.…”

“…Given the NP-hard nature of 2D-SPP, many (meta)heuristic procedures have been tried: Greedy Randomized Adaptive Search Procedure (GRASP) [6], Intensification / Diversification Walk (IDW) [7], Simulated Annealing [8,9,10,11], Tabu Search (TS) [8,12,13], Genetic Algorithm [9,10,11,13,14,15,16,17,18,19], hybrid (meta)heuristic [11,13,20], HyperHeuristic [21]. Exact algorithms have also been considered but they are usually limited to "small instances" (up to 200 objects) [22,23,24,25].…”

A Reinforced Tabu Search Approach for 2D Strip Packing

“…3.2). Among these strategies, the greedy randomized adaptive search procedure from Alvarez-Valdes et al (2008) and the hybrid hyperheuristic + intensification / diversification walk strategy from Neveu et al (2008) are probably the best performing ones for 2D-SPP (these two effective methods are briefly summarized in Sect. 3.2).…”

“…In this section, we review two best-performing algorithms and discuss about other representative heuristics related to 2D-SPP. Alvarez-Valdes et al (2008) proposed a Greedy Randomized Adaptive Search Procedure (GRASP) for 2D-SPP. It is a multi-start scheme that iteratively builds a feasible solution in a greedy way following various dynamic pseudo-random selection rules.…”