In this paper an upper bound strategy (UBS) is proposed for reducing the total number of structural analyses in metaheuristic based design optimization of steel frame structures. The well-known big bang鈥揵ig crunch algorithm as well as its two enhanced variants are adopted as typical ...
design for evaluating a candidate solution of the metaheuristic algorithm. This application also shows that it is the evaluation operator that may take a much longer computation time than all the other operators of a metaheuristic algorithm because a training process of DNN is required to evaluate ...
metaheuristic algorithmSonet network design problemoptical telecommunication network designring-based topologySonet ring assignment problemThis paper considers two problems that arise in the design of optical telecommunication networks when a ring-based topology is adopted, namely the SONET Ring Assignment ...
Thereafter Taguchis orthogonal design method is employed to solve the critical issues on the subject of parameters selection for the proposed metaheuristic algorithm. The adopted technique is therefore tested on 5 different datasets of size 5 9 to 27 9 and the obtained results are compared with C...
This new mechanism is used to intertwine a tabu search based primal intensive scheme with a Lagrangian based dual intensive scheme to design a dynamic primal-dual algorithm that progressively reduces the gap between upper and lower bound. The algorithm has been tested on benchmark problems from ...
In this section, we introduce a simple and effective strategy to enhance a nature-inspired swarm-based algorithm so that the enhanced algorithm is guaranteed to converge almost surely to a global optimum. We assume the cost function can be high-dimensional, non-differentiable, non-separable or no...
algorithm is a parameter-free optimization method since it doesn't require any additional parameter setup at any point throughout the optimization process. It seems urgently necessary to design a novel metaheuristic algorithm that is parameter-free and capable of solving any optimization problem without...
The algorithm is based on an incremental PID that converges the entire population to the optimal state by adjusting the system deviations. Advanced metaheuristic algorithms of recent years are selected for comparison with PSA, which include FHO, GJO, AOS, TSA, SOA, HHO, and SHO. The ...
A model predictive control (MPC) scheme has been implemented to design the controller; then, the DE algorithm is deployed to obtain the optimal path. The experimental results showed that the implementation can achieve suitable control performance for path planning in autonomous cars. However, no ...
The performance of the algorithm is based on the sequence of items. If the items are arranged in decreasing order, then the results are equivalent to that of BF-Decreasing, and if the items are arranged in increasing order, the algorithm will place small items into the initial bins. Larger...