Implementation and Optimization of cGA+LS to solve Capacitated VRP over Cell/B.E.

Abstract

This paper presents a case study to illustrate the design and implementation of cellular Genetic Algorithm (cGA) with Local Search (LS) to solve Capacitated Vehicle Routing Problem (CVRP) over Cell Broadband Engine (Cell BE). Cell BE is a heterogeneous, distributed memory multicore processor architecture for multimedia applications with regular memory access requirements. It has one 64-bit Power Processing Element (PPE) that acts as the main processor and 8 Synergistic Processing Elements (SPEs) with only 256 KB of local memory, each for instructions and data. GAs on the other hand use population based search techniques. Such techniques usually have large memory requirements and show non-uniform memory access patterns. These properties of GAs make their implementation over Cell BE even more challenging. In order to take maximum advantage of the hardware, we propose an asynchronous approach to implement cGA+LS over Cell BE. In this paper, we discuss the implementation and optimization of the proposed method in detail. We compare the proposed method with other state-of-theart CVRP solvers and synchronous implementation of cGA+LS over Cell BE. We solve existing benchmark problems and achieve considerable speedups. We extend the work further to solve extremely large instances of CVRP compared to ones present in the CVRP literature, and get acceptable results in a reasonable amount of time.