Traveling Salesman Problem (TSP) is one of the most widely studied real world problems of finding the shortest (minimum cost) possible route that visits each node in a given set of nodes (cities) once and then returns...Traveling Salesman Problem (TSP) is one of the most widely studied real world problems of finding the shortest (minimum cost) possible route that visits each node in a given set of nodes (cities) once and then returns to origin city. The optimization of cuboid areas has potential samples that can be adapted to real world. Cuboid surfaces of buildings, rooms, furniture etc. can be given as examples. Many optimization algorithms have been used in solution of optimization problems at present. Among them, meta-heuristic algorithms come first. In this study, ant colony optimization, one of meta-heuristic methods, is applied to solve Euclidian TSP consisting of nine different sized sets of nodes randomly placed on a cuboid surface. The performance of this method is shown in tests.展开更多
Studies have established that hybrid models outperform single models.The particle swarm algorithm(PSO)-based PID(proportional-integral-derivative)controller control system is used in this study to determine the parame...Studies have established that hybrid models outperform single models.The particle swarm algorithm(PSO)-based PID(proportional-integral-derivative)controller control system is used in this study to determine the parameters that directly impact the speed and performance of the Electro Search(ESO)algorithm to obtain the global optimum point.ESPID algorithm was created by integrating this system with the ESO algorithm.The improved ESPID algorithm has been applied to 7 multi-modal benchmark test functions.The acquired results were compared to those derived using the ESO,PSO,Atom Search Optimization(ASO),and Vector Space Model(VSM)algorithms.As a consequence,it was determined that the ESPID algorithm’s mean score was superior in all functions.Additionally,while comparing the mean duration value and standard deviations,it is observed that it is faster than the ESO algorithm and produces more accurate results than other algorithms.ESPID algorithm has been used for the least cost problem in the production of pressure vessels,which is one of the real-life pro-blems.Statistical results were compared with ESO,Genetic algorithm and ASO.ESPID was found to be superior to other methods with the least production cost value of 5885.452.展开更多
文摘Traveling Salesman Problem (TSP) is one of the most widely studied real world problems of finding the shortest (minimum cost) possible route that visits each node in a given set of nodes (cities) once and then returns to origin city. The optimization of cuboid areas has potential samples that can be adapted to real world. Cuboid surfaces of buildings, rooms, furniture etc. can be given as examples. Many optimization algorithms have been used in solution of optimization problems at present. Among them, meta-heuristic algorithms come first. In this study, ant colony optimization, one of meta-heuristic methods, is applied to solve Euclidian TSP consisting of nine different sized sets of nodes randomly placed on a cuboid surface. The performance of this method is shown in tests.
文摘Studies have established that hybrid models outperform single models.The particle swarm algorithm(PSO)-based PID(proportional-integral-derivative)controller control system is used in this study to determine the parameters that directly impact the speed and performance of the Electro Search(ESO)algorithm to obtain the global optimum point.ESPID algorithm was created by integrating this system with the ESO algorithm.The improved ESPID algorithm has been applied to 7 multi-modal benchmark test functions.The acquired results were compared to those derived using the ESO,PSO,Atom Search Optimization(ASO),and Vector Space Model(VSM)algorithms.As a consequence,it was determined that the ESPID algorithm’s mean score was superior in all functions.Additionally,while comparing the mean duration value and standard deviations,it is observed that it is faster than the ESO algorithm and produces more accurate results than other algorithms.ESPID algorithm has been used for the least cost problem in the production of pressure vessels,which is one of the real-life pro-blems.Statistical results were compared with ESO,Genetic algorithm and ASO.ESPID was found to be superior to other methods with the least production cost value of 5885.452.
