TTTPLOTS: A perl program to create time-to-target plots

ABSTRACT. 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, and GRASP. Such plots are very useful in the comparison of different algorithms or strategies for solving a given problem and have been widely used as a tool for algorithm design and comparison. We first discuss how TTT plots are generated. This is followed by a description of the perl program tttplots.pl. 1

Parallel Grasp With Path-Relinking For Job Shop Scheduling

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 must complete processing without interruption. A schedule is an assignment of operations to time slots on the machines. The objective of the JSP is to find a schedule that minimizes the maximum completion time, or makespan, of the jobs. In this paper, we describe a parallel greedy randomized adaptive search procedure (GRASP) with path-relinking for the JSP. A GRASP is a 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 intensification strategy that explores trajectories that connect high quality solutions. Independent and cooperative parallelization strategies are described and implemented. Computational experience on a large set of standard test problems indicates that the parallel GRASP with path-relinking finds goodquality approximate solutions of the job shop scheduling problem

Probability Distribution Of Solution Time In Grasp: An Experimental Investigation

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 independent runs of the heuristic. Standard methodology for graphical analysis is used to compare the empirical and theoretical distributions and estimate the parameters of the distributions. We conclude that the solution time to a sub-optimal target value fits a two-parameter exponential distribution. Hence, it is possible to achieve linear speed-up by implementing GRASP in parallel

GRASP with path relinking for three-index assignment

Abstract. This paper describes variants of GRASP (greedy randomized adap-tive search procedure) with path relinking for the three index assignment problem (AP3). GRASP is a multi-start metaheuristic for combinatorial op-timization. It usually consists of a construction procedure based on a greedy randomized algorithm and of a local search. Path relinking is an intensifi-cation strategy that explores trajectories that connect high quality solutions. Several variants of the heuristic are proposed and tested. Computational re-sults show clearly that this GRASP for AP3 benefits from path relinking and that the variants considered in this paper compare well with previously pro-posed heuristics for this problem. GRASP with path relinking was able to improve the solution quality of heuristics proposed by Balas and Saltzman (1991), Burkard, Rudolf, and Woeginger (1996), and Crama and Spieksma (1992) on all instances proposed in those papers. We show that the random variable “time to target solution, ” for all proposed GRASP with path relinking variants, fits a two-parameter exponential distribution. To illustrate the con-sequence of this, one of the variants of GRASP with path relinking is shown to benefit from parallelization. 1

Cooperative Multi-Thread Parallel Tabu Search with an Application to Circuit Partitioning

. 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 different variant of a sequential tabu search algorithm, using a different combination of initial solution algorithm and move attribute definition. These threads communicate by exchanging elite solutions. PVM and Linda are used in the implementation of the parallel tabu search procedure. Numerical results reported for a set of ISCAS benchmark circuits illustrate the effectiveness of the parallel tabu search procedure. Comparative results illustrating the efficiency of the implementations in PVM and Linda are also assessed. 1 Introduction The logical test of integrated VLSI circuits is one of the main phases of their design and fabrication. Testing a circuit amounts to submitting it to different input patterns and checking whether the observed outputs are exactly those e..