A comparison of semi-deterministic and stochastic search techniques
This work addresses optimization challenges in engineering design, but it is incremental as it compares existing methods without introducing new ones.
The paper compared tabu search and simulated annealing for engineering design optimization, finding that both techniques outperformed steepest descent on a structural optimization problem.
This paper presents an investigation of two search techniques, tabu search (TS) and simulated annealing (SA), to assess their relative merits when applied to engineering design optimisation. Design optimisation problems are generally characterised as having multi-modal search spaces and discontinuities making global optimisation techniques beneficial. Both techniques claim to be capable of locating globally optimum solutions on a range of problems but this capability is derived from different underlying philosophies. While tabu search uses a semi-deterministic approach to escape local optima, simulated annealing uses a complete stochastic approach. The performance of each technique is investigated using a structural optimisation problem. These performances are then compared to each other as and to a steepest descent (SD) method.