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.
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.