Herein, we propose a piecewise-linear particle swarm optimizer (PPSO).PPSO is one of the deterministic PSO, which has two search dynamics, a convergence mode and a divergence mode.Solving performances of PPSO are significantly affected by connective coefficient γ.We investigate relations between solving performances and the connective coefficient, and reveal a method of setting the connective coefficient according to the structure of a solution space.We further compare the solving performances of PPSO with those of other deterministic PSO methods and classic PSO in the numerical experiments.

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We propose two optimization benchmark problems with actual engineering design features of car-body structural development using response surface method. The first is a single-objective optimization problem of weight minimization. The second is the multi-objective optimization problem of weight minimization and number of common thickness parts maximization. These benchmark problems have key feature of real-world design problem, i.e. many variables and many constraint conditions. Furthermore, it is a discrete variable optimization problem. We present optimization results using multi-island genetic algorithm (single-objective optimization) and NSGA-II (multiobjective optimization). We also present optimization result of the benchmark problem where the discrete variables are treated as real variables. The benchmark problem is available on http://ladse.eng.isas.jaxa.jp/benchmark.

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