Solving constrained multilocal optimization problems with parallel stretched simulated annealing

Constrained multilocal programming optimization problems may be solved by solving a sequence of unconstrained problems. In turn, those unconstrained problems may be solved using techniques like the Stretched Simulated Annealing (SSA) method. In order to increase the solving performance and make possible the discovery of new optima, parallel approaches to SSA have been devised, like Parallel Stretched Simulated Annealing (PSSA). Recently, Constrained PSSA (coPSSA) was also proposed, coupling the penalty method with PSSA, in order to solve constrained problems. In this work, coPSSA is explored to solve four test problems using the l 1 penalty function. The effect of the variation of the reduction factor parameter of the l 1 penalty function is also studied.This work was been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the project UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

coPSSA - constrained parallel stretched simulated annealing

Parallel Stretched Simulated Annealing (PSSA) solves unconstrained multilocal programming optimization problems in distributed memory clusters, by applying the Stretched Simulated Annealing optimization method, in parallel, to multiple sub-domains of the original feasible region. This work presents coPSSA (constrained Parallel Stretched Simulated Annealing), an hybrid application that combines shared memory based parallelism with PSSA, in order to efficiently solve constrained multilocal programming problems. We devise and evaluate two different parallel strategies for the search of solutions to these problems. Evaluation results from a small set of test problems often reach superlinear speedup in the solution search time, thus proving the merit of the coPSSA parallelization approach

Solving multilocal optimization problems with a recursive parallel search of the feasible region

Stretched Simulated Annealing (SSA) combines simulated annealing with a stretching function technique, in order to solve multilocal programming problems. This work explores an approach to the parallelization of SSA, named PSSA-HeD, based on a recursive heterogeneous decomposition of the feasible region and the dynamic distribution of the resulting subdomains by the processors involved. Three PSSAHeD variants were implemented and evaluated, with distinct limits on the recursive search depth, offering different levels of numerical and computational efficiency. Numerical results are presented and discussed.This work was been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the project PEst-OE/EEI/UI0319/2014

XVI Congresso da Associação Portuguesa de Investigação Operacional: livro de resumos

Fundação para a Ciência e a Tecnologia - FC

Livro de atas do XVI Congresso da Associação Portuguesa de Investigação Operacional

Fundação para a Ciência e Tecnologia - FC