Simulated annealing based symbiotic organisms search optimization algorithm for traveling salesman problem

Symbiotic Organisms Search (SOS) algorithm is an effective new metaheuristic search algorithm, which has recently recorded wider application in solving complex optimization problems. SOS mimics the symbiotic relationship strategies adopted by organisms in the ecosystem for survival. This paper, presents a study on the application of SOS with Simulated Annealing (SA) to solve the well-known traveling salesman problems (TSPs). The TSP is known to be NP-hard, which consist of a set of (n − 1)!/2 feasible solutions. The intent of the proposed hybrid method is to evaluate the convergence behaviour and scalability of the symbiotic organism’s search with simulated annealing to solve both small and large-scale travelling salesman problems. The implementation of the SA based SOS (SOS-SA) algorithm was done in the MATLAB environment. To inspect the performance of the proposed hybrid optimization method, experiments on the solution convergence, average execution time, and percentage deviations of both the best and average solutions to the best known solution were conducted. Similarly, in order to obtain unbiased and comprehensive comparisons, descriptive statistics such as mean, standard deviation, minimum, maximum and range were used to describe each of the algorithms, in the analysis section. The oneway ANOVA and Kruskal-Wallis test were further used to compare the significant difference in performance between SOS-SA and the other selected state-of-the-art algorithms. The performances of SOS-SA and SOS are evaluated on different sets of TSP benchmarks obtained from TSPLIB (a library containing samples of TSP instances). The empirical analysis’ results show that the quality of the final results as well as the convergence rate of the new algorithm in some cases produced even more superior solutions than the best known TSP benchmarked results

Performance of coated, cemented carbide, mixed-ceramic and PCBN-H tools when turning W320 steel

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)TiN-coated cemented carbide, mixed ceramic and PCBN with a high percentage of CBN (PCBN-H) tools were used for reconditioned turning of hardened and tempered W320 steel hot working dies. The dies are usually scraped after their useful life because they are difficult to be reconditioned by machining. One alternative to scraping these dies is to convert them, increasing their internal diameters by internal turning. The machining experiments showed that coated carbide tools performed better at cutting speeds up to 120 m/min, while PCBN tools were superior at higher speeds up to 200 m/min. Mixed ceramic tools did not perform well under the conditions investigated. The tribological system showed abrasion, adhesion and plastic deformation as the dominant wear mechanisms. Chipping on the tool rake and flank faces, as well as catastrophic failure, was also observed in some experiments.4141858660669Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)CDTN (Centro Nacional de Tecnologia Nuclear)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)CAPES [PDE 0333-04-2

Probe Machine Based Consecutive Route Filtering Approach to Symmetric Travelling Salesman Problem

Part 6: Intelligent RobotInternational audienceThe travelling salesman problem (TSP) is one of the NPC combinatorial optimization problems and still now it remains as an interesting and challenging problem in the field of combinatorial optimization. In this paper, we propose a consecutive route filtering approach to solving the symmetric TSP with the help of probe concept such that the worse routes are filtered out step by step by using a rigorous predesigned step proportion. In this way, it is important to set up a reasonable value of the step proportion which is needed in each step during the filtering process. Actually, our proposed algorithm is implemented on the set of symmetric TSP benchmarks with both small and large numbers of cities from the TSPLIB dataset. It is demonstrated by the experimental results that our proposed algorithm can obtain the best results in some cases and generally get the approximation results close to the best known solutions