A Parametric Framework for Cooperative Parallel Local Search

Abstract

Abstract. In this paper we address the problem of parallelizing local search. We propose a general framework where different local search engines cooperate (through communication) in the quest for a solution. Several parameters allow the user to instantiate and customize the framework, like the degree of intensification and diversification. We implemented a prototype in the X10 programming language based on the adaptive search method. We decided to use X10 in order to benefit from its ease of use and the architectural independence from parallel resources which it offers. Initial experiments prove the approach to be successful, as it outperforms previous systems as the number of processes increases.

On Integrating Population-Based Metaheuristics with Cooperative Parallelism

“…The Cooperative Parallel Local Search framework (CPLS) [15], [16] was designed to facilitate the implementation of cooperative parallel local search solvers. CPLS is available as an open source library written in the IBM X10 concurrent programming language.…”

“…However, a welltuned cooperation scheme may significantly outperform the independent approach. To this end, a framework -called CPLS -which eases the cooperative parallelization of local search solvers has been recently proposed in [15], [16]. This framework, available as an open source library written in the IBM X10 concurrent programming language, allows the programmer to tune the search process through an extensive set of parameters.…”

Solving the Quadratic Assignment Problem with Cooperative Parallel Extremal Optimization

“…We build on the framework for Cooperative Parallel Local Search (CPLS) proposed in [29,7]. This framework, available as an open source library in the X10 programming language, allows the programmer to tune the search process through an extensive set of parameters which, in the present version, statically condition the execution.…”

“…The resulting solver is then composed of several EO-QAP instances running in parallel, which cooperate by communicating in order to converge faster on a solution. As per [7], the CPLS parameters which control the cooperation are as follows:…”

“…Secondly, we propose to use cooperative parallelism to promote more intensification and/or diversification. Our implementation uses a parallel framework [7] written in X10 [8,9]. We show that the cooperative parallel version behaves very well on the hardest instances.…”