Tabu Search on GPU

Nowadays personal computers (pcs) are often equipped with powerful, multi-core cpu. however, the processing power of the modern pc does not depend only of the processing power of the cpu and can be increased by proper use of the gpgpu, i.e. general-purpose computation using graphics hardware. modern graphics hardware, initially developed for computer graphics generation, appeared to be flexible enough for general-purpose computations. in this paper we present the implementation of two optimization algorithms based on the tabu search technique, namely for the traveling salsesman problem and the flow shop scheduling problem. both algorithms are implemented in two versions and utilize, respectively, multi-core cpu, and gpu. the extensive numerical experiments confirm the high computation power of gpu and show that tabu search algorithm run on modern gpu can be even 16 times faster than run on modern cpu.