Co-operation in the Parallel Memetic Algorithm

Abstract

Evolutionary algorithms (EAs) have been attracting research attention for last decades. They were shown to be very efficient in solving various complex optimization problems in most fields of science and engineering. In EAs, the population of solutions evolves in time to explore the search space. Parallel EAs became an important stream of development due to a wide availability of parallel computer architectures. Thus, designing parallel algorithms utilizing hundreds of CPU cores efficiently is critical nowadays. In this paper, we investigate the impact of selecting a cooperation scheme for the parallel memetic algorithm (PMA-VRPTW) to solve the NP-hard vehicle routing problem with time windows. In the island-model PMA-VRPTW, which is a hybrid of a genetic algorithm applied to explore the search space, and some refinement methods to exploit solutions already found, a number of populations are evolved in parallel. Processes then cooperate and exchange solutions according to the cooperation scheme (migration policy, interval, and topology). Extensive experimental study (which comprised more than 1,584,000 CPU hours on an SMP cluster) performed on 1000-customer Gehring and Homberger's (GH) benchmark tests gave a detailed insight into the PMA-VRPTW performance and search capabilities. We report 19 (32 % of all 1000-customer GH tests) new world's best solutions obtained using the best cooperation schemes. Finally, we give clear and consistent guidelines on how to select a proper cooperation scheme in PMA-VRPTW based on the test characteristics.

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“…In this case, γ = 0.95, and this parameter is used in the way as can be seen in Equ. (22). This parameter has been set following the guidelines proposed in several studies of the literature [56,31].…”

Is Your Parallel Algorithm Correct?

“…Parallel heuristic algorithms have been explored for solving a bunch of different optimization problems [24], including various VRPs [21], [25]. Co-operative strategies in such parallel heuristic techniques have been discussed and classified in several taxonomies, with the one presented by Crainic et al being the best established [26], which encompasses three dimensions.…”

Real-Time People Counting from Depth Images

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“…It results in decreasing the operational costs of transport operators by optimizing routing schedules. This also affects the traffic congestion and environmental pollution which are very important concerns nowadays [15].…”