4.1 Heuristic and metaheuristic algorithm The heuristic algorithms are a kind of intuitively or empirically constructed algorithms that give a feasible solution for specific problems to be solved. Metaheuristic algorithms are the improvement of heuristic algorithms, which is the combination of random algorit...
First, we develop a new metaheuristic for the SVPP, which greatly improves upon previous literature and solves industrial supply vessel planning problems of realistic size. Second, by adapting the HGSADC to the SVPP, we demonstrate new possibilities of extensions to account for routes (voyages in...
Innovations in Edge and Fog Computing for Enhanced Medical Analysis have the potential to radically alter the healthcare system [1]. This area, however, has its own set of difficulties typical of new technologies. Privacy and security of personal information is a major issue. Information of a m...
where\(f(X)\)is the objective function, design vector is the n-dimensional vector X,\({g}_{j}(X)\)signifies inequality constraints and\({l}_{j}(X)\)signifies equality constraints respectively. The goal of this study is to analyse metaheuristic optimization for the solution for VRP probl...
Finally, we compare the results with those found by our implementation of the PTMC algorithm for the conformational search problem, a state-of-the-art metaheuristic for conformational sampling. Details of the parameters used for VND, the quantum annealer, and PTMC are presented in the Supplementary...
whereas hyper-heuristics search the spaceSof heuristics. In practice this means that a metaheuristic can have access to problem specific information, while a hyper-heuristic is subject to the limitations of thedomain barrierand is unable to access problem specific information. The domain barrier requir...
[9] which is a metaheuristic method to solve a research problem. In addition, to analyze the effect of HM components on the quality of the solution, three HM variables were compared, and the results were compared with the proposed method. GA-FSGS: FSGS without VNS is embedded in GA. ...
The developed heuristic tool obtains an initial feasible solution using a greedy algorithm and then uses the simulated annealing metaheuristic to improve the solution, which is a measure of physician satisfaction. The heuristic tool developed in this study was tested using eight randomly generated data...
In order to test the efficiency of the proposed heuristic, two metaheuristic algorithms are applied: particle swarm optimization (PSO) and differential evolution (DE). Additionally, two numerical examples were solved. In the first one, it is shown that the proposed heuristic performed best compared...
We refer to the time difference between the time window and the service time as the slack in the time window. For example, instead of always choosing the node and location with the lowest cost as the next insertion, it may be better to select an insertion, which does not use much of ...