On practical resource allocation for production planning and scheduling with period overlapping setups

“…The purpose of this work is twofold. Its first goal is to apply a fix-and-relax (FR) heuristic [13] to the MILP CTA problem. Briefly, FR partitions the set of binary variables into k clusters, and iteratively optimizes for each cluster i = 1, .…”

Section: Introductionmentioning

confidence: 99%

“…FR has been successfully applied in the past mainly to scheduling problems [13,15,16]. In those applications, variables and constraints can naturally be partitioned according to some sequential stages, two consecutive ones being only linked by a few of the variables and constraints of each partition.…”

Section: Introductionmentioning

confidence: 99%

Fix-and-relax approaches for controlled tabular adjustment

Baena

Castro

González

2015

Computers & Operations Research

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Controlled tabular adjustment (CTA) is a relatively new protection technique for tabular data protection. CTA formulates a mixed integer linear programming problem, which is challenging for tables of moderate size. Even finding a feasible initial solution may be a challenging task for large instances. On the other hand, end users of tabular data protection techniques give priority to fast executions and are thus satisfied in practice with suboptimal solutions. This work has two goals. First, the fix-and-relax (FR) strategy is applied to obtain good feasible initial solutions to large CTA instances. FR is based on partitioning the set of binary variables into clusters to selectively explore a smaller branch-and-cut tree. Secondly, the FR solution is used as a warm start for a block coordinate descent (BCD) heuristic (approach named FR+BCD); BCD was confirmed to be a good option for large CTA instances in an earlier paper by the second and third co-authors (Computers & Operations Research 2011). We report extensive computational results on a set of real-world and synthetic CTA instances. FR is shown to be competitive compared to CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound. FR+BCD improved the quality of FR solutions for approximately 25% and 50% of the synthetic and real-world instances, respectively. FR or FR+BCD provided similar or better solutions in less CPU time than CPLEX for 73% of the difficult real-world instances.

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“…A heuristic cutting planes method was developed by Mokotoff and Chretienne (2002) that was later refined and extended in what is known as the "Partial" method in Mokotoff and Jimeno (2002). This algorithm is based on the methodology of Dillenberger et al (1994) which was later used by Mansini and Speranza (1999). Woclaw (2006) carried out a comprehensive re-implementation and a computational evaluation of most existing literature for the R//C max , and showed that the Partial method of Mokotoff and Jimeno (2002) produced state-of-the-art results, surpassing all other tested methods.…”

Section: Introductionmentioning

confidence: 99%

Size-reduction heuristics for the unrelated parallel machines scheduling problem

Fanjul-Peyro

Ruíz

2011

Computers & Operations Research

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In this paper we study the unrelated parallel machines problem where n independent jobs must be assigned to one out of m parallel machines and the processing time of each job differs from machine to machine. We deal with the objective of the minimisation of the maximum completion time of the jobs, usually referred to as makespan or C max . This is a type of assignment problem that has been frequently studied in the scientific literature due to its many potential applications. We propose a set of metaheuristics based on a size-reduction of the original assignment problem that produce solutions of very good quality in a short amount of time. The underlying idea is to consider only a few of the best possible machine assignments for the jobs and not all of them. The results are simple, yet powerful methods. We test the proposed algorithms with a large benchmark of instances and compare them with current state-of-the-art methods. In most cases, the proposed size-reduction algorithms produce results that are statistically proven to be better by a significant margin.

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On practical resource allocation for production planning and scheduling with period overlapping setups

Cited by 136 publications

References 4 publications

Lot sizing and scheduling with sequence-dependent setup costs and times and efficient rescheduling opportunities

Lot sizing and scheduling with sequence-dependent setup costs and times and efficient rescheduling opportunities

Fix-and-relax approaches for controlled tabular adjustment

Size-reduction heuristics for the unrelated parallel machines scheduling problem

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