An optimization-based heuristic for the machine reassignment problem

Abstract

We address the machine reassignment problem proposed in the context of the ROADEF/EURO challenge 2012 in partnership with Google. The problem consists in reassigning a set of processes to a set of multiple-resource machines so as to minimize a weighted function of the machines load, the resources balance, and the costs of moving processes while satisfying numerous constraints. We propose an optimization-based heuristic that requires decomposing the problem into a sequence of small-sized instances that are iteratively solved using a general MIP solver. To speed-up the solution process several algorithmic expedients are embedded. Extensive computational experiments provide evidence that the proposed approach exhibits a very good performance.

A Survey and a Classification of Recent Approaches to Solve the Google Machine Reassignment Problem

“…In [18], an optimization-based heuristic technique was proposed (OBH-S27). This technique requires the decomposition of the problem into a sequence of small-sized instances, that are iteratively solved using a general Mixed Integer Programming (MIP) solver.…”

“…Table 7 shows the best known quality solution per instance considering the same experimental setup of the challenge (execution time limit and sequential execution). Here, the algorithms that obtained at least one best known quality solution are VNS [7], LNS-CP [9], LNS-MIP [9], MS-ILS [10], HC-LNSHC [15], MNLS [17], OBH-S25 [18], SD-Combined [19] and IP-RILS [16]. The algorithms that obtained the highest number of best known solutions are VNS [7] (12 instances), followed by MNLS [17] (7 instances) and HC-LNSHC [15] (6 instances).…”

“…Here, in most cases, the total cost for each instance is lower than when the experimental setup of the challenge is considered. The algorithms VNS [7], SA-GMRP [20], LNS-CP [9], LNS-MIP [9], MS-ILS [10], NLS [24], HC-LNSHC [15], P-LAHC [27], MNLS [17], OBH-S25 [18], SD-Combined [19], MNGD [30], ESA [29], CHSA [8], HH [31] and Ant-HH [32] obtained at least one best known quality solution. Moreover, the algorithms that reached the highest number of best known solutions are Ant-HH [32] (23 instances), HH [31] (5 instances), NLS [24] (4 instances) and VNS [7] (3 instances).…”

Serviços, Processos E Máquinas: Um Estudo De Metodologias Para Realocação De Processos Nas Máquinas

“…Aplica-se então uma otimização no sub problema. Um método parecido é apresentado em (Jaskowski et al, 2015) e em (Mrad et al, 2015).…”