A Tabu Search Algorithm for Scheduling Independent Jobs in Computational Grids

The efficient allocation of jobs to grid resources is indispensable for high performance grid-based applications, and it is a computationally hard problem even when there are no dependencies among jobs.We present in this paper a new tabu search (TS) algorithm for the problem of batch job scheduling on computational grids. We define it as a bi-objective optimization problem, consisting of the minimization of the makespan and flowtime. Our TS is validated versus three other algorithms in the literature for a classical benchmark. We additionally consider some more realistic benchmarks with larger size instances in static and dynamic environments. We show that our TS clearly outperforms the compared algorithms

An overview of neighbourhood search metaheuristics

This paper gives details of the steps needed to undertake neighbourhood search for a combinatorial optimization problem. The main variations are briefly described and pointers for future research briefly discussed. Throughout there is extensive referencing to some of the most important publications in the are

Parallelizing Tabu Search on a Cluster of HeterogeneousWorkstations

In this paper, we present the parallelization of tabu search on a network of workstations using PVM. Two parallelization strategies are integrated: functional decomposition strategy and multi-search threads strategy. In addition, domain decomposition strategy is implemented probabilistically. The performance of each strategy is observed and analyzed. The goal of parallelization is to speedup the search in finding better quality solutions. Observations support that both parallelization strategies are beneficial, with functional decomposition producing slightly better results. Experiments were conducted for the VLSI cell placement, an NP-hard problem, and the objective was to achieve the best possible solution in terms of interconnection length, timing performance (circuit speed), and area. The multiobjective nature of this problem is addressed using a fuzzy goal-based cost computation. Key Words: tabu search, parallel tabu search, metaheuristic, functional decomposition, multi-search threads, combinatorial optimization, VLSI, standard cell design, placement, fuzzy logi