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- Renata M. Aiex, S. Binato, Mauricio G. C. Resende
- Parallel Computing
- 2003

In the job shop scheduling problem (JSP), a finite set of jobs is processed on a finite set of machines. Each job is required to complete a set of operations in a fixed order. Each operation is processed on a specific machine for a fixed duration. A machine can process no more than one job at a time and once a job initiates processing on a given machine it… (More)

- Renata M. Aiex, Mauricio G. C. Resende, Panos M. Pardalos, Gerardo Toraldo
- INFORMS Journal on Computing
- 2005

T paper proposes and tests variants of GRASP (greedy randomized adaptive search procedure) with path relinking for the three-index assignment problem (AP3). GRASP is a multistart metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and of a local search. Path relinking is an… (More)

- Renata M. Aiex, Mauricio G. C. Resende, Celso C. Ribeiro
- J. Heuristics
- 2002

Abstract. A GRASP (greedy randomized adaptive search procedure) is a multi-start metaheuristic for combinatorial optimization. We study the probability distributions of solution time to a sub-optimal target value in five GRASPs that have appeared in the literature and for which source code is available. The distributions are estimated by running 12,000… (More)

- Renata M. Aiex, Mauricio G. C. Resende, Celso C. Ribeiro
- Optimization Letters
- 2007

This papers describes a perl language program to create time-to-target solution value plots for measured CPU times that are assumed to fit a shifted exponential distribution. This is often the case in local search based heuristics for combinatorial optimization, such as simulated annealing, genetic algorithms, iterated local search, tabu search, WalkSAT,… (More)

- RENATA M. AIEX
- 2003

A Greedy Randomized Adaptive Search Procedure (GRASP) is a metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and local search. Path-relinking is an intensification strategy that explores trajectories that connect high quality solutions. We analyze two parallel strategies for… (More)

- Renata M. Aiex, Panos M. Pardalos, Leonidas S. Pitsoulis, Mauricio G. C. Resende
- IPDPS Workshops
- 2000

In this talk a greedy randomized adaptive search procedure (GRASP) is presented for computing approximate solutions to the NP-hard three-index assignment problem (AP3). A FORTRAN implementation of this GRASP is tested on several problem instances of the AP3. A parallelization strategy that combines GRASP and path relinking is also proposed and tested for… (More)

- Renata M. Aiex, Simone L. Martins, Celso C. Ribeiro, Noemi de La Rocque Rodriguez
- IRREGULAR
- 1998

In this work, we propose a cooperative multi-thread parallel tabu search heuristic for the circuit partitioning problem. This procedure is based on the cooperation of multiple search threads. Each thread implements a diierent variant of a sequential tabu search algorithm, using a diierent combination of initial solution algorithm and move attribute… (More)

- Renata M. Aiex
- EUROSIM
- 1996

Search algorithms for the Detection of Irregular Structures are extremely diicult to parallelize eeciently, due to their non-local nature that makes load balancing a major problem. In this work some algorithms are investigated and implemented for Multiple Cluster and Single Cluster Search problems. A new (asynchronous) approach for the Single Cluster Search… (More)

In this paper, we describe a methodology for the analysis of greedy randomized adaptive search procedures (GRASP). GRASP is a metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and a local search. Hybrid approaches of GRASP with path-relinking developed for the 3-index… (More)

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