In order to improve the efficiency of test data generation during the software test, many studies have been focusing on the automation of test data generation with metaheuristic techniques such as genetic algorithm and tabu search etc. This paper proposes a hybrid algorithm in combination with genetic algorithm with tabu search to generate the test data based on decision coverage criteria. The ...

We propose a powerful Reinforced Hybrid Genetic Algorithm (RHGA) for the famous NP-hard Traveling Salesman Problem (TSP). RHGA combines reinforcement learning technique with well-known Edge Assembly Crossover genetic algorithm (EAX-GA) and Lin-Kernighan-Helsgaun (LKH) local search heuristic. With help of proposed hybrid mechanism, evolution EAX-GA LKH can boost each other's performance. And bas...

tomato as a highly nutritious vegetable crop is widely grown in the world. hybrid seed is preferably used for tomato production. identification of superior hybrid combination is one of the most important steps in the hybrid breeding programs. breeding of high yielding hybrids is expensive and involves testing large numbers of hybrid combinations in multi-environment trials. successful predictio...

The paper describes a comparative study of multiple-objective metaheuristics on the bi-objective set covering problem. Ten representative methods based on genetic algorithms, multiple start local search, hybrid genetic algorithms and simulated annealing are evaluated in the computational experiment. Nine of the methods are well known from the literature. The paper introduces also a new hybrid g...

An integer program and a hybrid genetic algorithm for the university timetabling problem Xuehao Feng, Yuna Lee & Ilkyeong Moon To cite this article: Xuehao Feng, Yuna Lee & Ilkyeong Moon (2017) An integer program and a hybrid genetic algorithm for the university timetabling problem, Optimization Methods and Software, 32:3, 625-649, DOI: 10.1080/10556788.2016.1233970 To link to this article: htt...

this with the integration of distributed generation (dg) to meshed distribution systems, the operating time of the protective system becomes a major concern in order to avoid nuisance dg tripping. this paper proposes a new tripping characteristic for directional overcurrent relays (docrs) that can achieve a higher possible reduction of overall relays operating time in meshed distribution networ...

Hybrid genetic algorithms have received significant interest in recent years and are being increasingly used to solve real-world problems. A genetic algorithm is able to incorporate other techniques within its framework to produce a hybrid that reaps the best from the combination. In this paper, different forms of integration between genetic algorithms and other search and optimization techniqu...

Genetic Algorithms are biologically inspired optimization algorithms. Performance of genetic algorithms mainly depends on type of genetic operators – Selection, Crossover, Mutation and Replacement used in it. Crossover operators are used to bring diversity in the population. This paper studies different crossover operators and then proposes a hybrid crossover operator that incorporates knowledg...