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 graph- ics hardware, initially developed for computer graphics generation, appeared to be flexible enough for general-purpose computations. In this paper we present the imple- mentation of two optimization algorithms based on the tabu search technique, namely for the traveling salsesman problem and the flow shop scheduling problem. Both algo- rithms 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.
[1]
Sebastien St-Laurent.
The Complete Effect and Hlsl Guide
,
2005
.
[2]
Eugeniusz Nowicki,et al.
The flow shop with parallel machines: A tabu search approach
,
1998,
Eur. J. Oper. Res..
[3]
Randima Fernando,et al.
The CG Tutorial: The Definitive Guide to Programmable Real-Time Graphics
,
2003
.
[4]
É. Taillard.
Some efficient heuristic methods for the flow shop sequencing problem
,
1990
.
[5]
Fred Glover,et al.
Tabu Search - Part II
,
1989,
INFORMS J. Comput..
[6]
Jens H. Krüger,et al.
A Survey of General‐Purpose Computation on Graphics Hardware
,
2007,
Eurographics.
[7]
Ceyda Oguz,et al.
Hybrid flow-shop scheduling problems with multiprocessor task systems
,
2004,
Eur. J. Oper. Res..