Random-key cuckoo search for the travelling salesman problem

Combinatorial optimization problems are typically NP-hard, and thus very challenging to solve. In this paper, we present the random key cuckoo search (RKCS) algorithm for solving the famous Travelling Salesman Problem (TSP). We used a simplified random-key encoding scheme to pass from a continuous space (real numbers) to a combinatorial space. We also consider the displacement of a solution in both spaces using L\'evy flights. The performance of the proposed RKCS is tested against a set of benchmarks of symmetric TSP from the well-known TSPLIB library. The results of the tests show that RKCS is superior to some other metaheuristic algorithms

Random-key cuckoo search for the travelling salesman problem

Combinatorial optimization problems are typically NP-hard, and thus very challenging to solve. In this paper, we present the random key cuckoo search (RKCS) algorithm for solving the famous Travelling Salesman Problem (TSP). We used a simplified random-key encoding scheme to pass from a continuous space (real numbers) to a combinatorial space. We also consider the displacement of a solution in both spaces using L\'evy flights. The performance of the proposed RKCS is tested against a set of benchmarks of symmetric TSP from the well-known TSPLIB library. The results of the tests show that RKCS is superior to some other metaheuristic algorithms

Performance of the bison algorithm on benchmark IEEE CEC 2017

This paper studies the performance of a newly developed optimization algorithm inspired by the behavior of bison herds: the Bison Algorithm. The algorithm divides its population into two groups. The exploiting group simulates the swarming behavior of bison herds endangered by predators. The exploring group systematically runs through the search space in order to avoid local optima. At the beginning of the paper, the Bison Algorithm is introduced. Then the performance of the algorithm is compared to the Particle Swarm Optimization and the Cuckoo Search on the set of 30 benchmark functions of IEEE CEC 2017. Finally, the outcome of the experiments is discussed. © 2019, Springer International Publishing AG, part of Springer Nature

New running technique for the bison algorithm

This paper examines the performance of the Bison Algorithm with a new running technique. The Bison Algorithm was inspired by the typical behavior of bison herds: the swarming movement of endangered bison as the exploitation factor and the running as the exploration phase of the optimization. While the original running procedure allowed the running groupto scatter throughout the search space, the new approach proposed in this paper preserves the initial formation of the running group throughout the optimization process. At the beginning of the paper, we introduce the Bison Algorithm and explain the new running technique procedure. Later the performance of the adjusted algorithm is tested and compared to the Particle Swarm Optimization and the Cuckoo Search algorithm on the IEEE CEC 2017 benchmark set, consisting of 30 functions. Finally, we evaluate the meaning of the experiment outcomes for future research. © Springer International Publishing AG, part of Springer Nature 2018.IC1406, COST, European Cooperation in Science and Technology; CA15140, COST, European Cooperation in Science and Technology; IGA/CebiaTech/2018/003; MSMT-7778/2014, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; LO1303, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; CZ.1.05/2.1.00/03.0089, FEDER, European Regional Development Fund; COST, European Cooperation in Science and TechnologyMinistry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2018/003]; COST (European Cooperation in Science and Technology)European Cooperation in Science and Technology (COST) [CA15140, IC1406

Working cycle sequence optimization for industrial robots

Trajectory optimization of a robotic work cell plays a fundamental role in productivity improvement. However, in some specific applications, such as robotic deburring, it is also possible to reduce cycle time by finding the best task order. In this paper, the well known Travelling Salesman Problem has been provided by additional constraints in order to solve the problem mentioned above. Moreover, such an approach has been applied to a specific industrial task