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Crossover methods are important keys to the success of genetic algorithms. However, traditional crossover methods fail to solve a trap problem, which is a difficult benchmark problem designed to deceive genetic algorithms to favor all-zero bits, while the actual solution is all-one bits. The Bayesian optimization algorithm (BOA) is the most famous algorithm that can solve the trap problem; however,...
This paper proposed an improvement of genetic algorithm for optimization problem. In this study, the Gaussian function is applied in crossover and mutation operators instead of traditional crossover and mutation. The algorithm is tested on five benchmark problems and compared with the self-adaptive DE algorithm, traditional differential evolution (DE) algorithm, the JDE self-adaptive algorithm and...
This paper proposes a method for tuning compilations to improve the size, execution time and reliability of the final application altogether. Our approach implements a genetic strategy with a multi-objective evolution that takes advantage of the NSGA-II algorithm for selecting the best compilations. Experiments show that reliability can be improved by efficiently exploring the compiler optimization...
Genetic Algorithm (GA) is a very popular evolutionary technique that has been used for single and multi-objective optimization problems. MATLAB, a widely used technical computing language, has its own variant of these algorithms included along with its optimization toolbox. Since this allows for easy implementation, it has been widely used to solve various engineering problems. The performances of...
Power consumption of VLSI has become a leading design concern with the growth of complexity and density. Leakage power reduces battery life for the entire portable battery operated devices. Many techniques have been projected to reduce the leakage power consumption, but most of these approaches require the process technology support. Input Vector Control is one of the approaches used for static power...
Some of the engineering applications warrant the solution of Graph Coloring Problem. This paper investigates a new genetic procedure using divide and conquer strategy on some of the intermediate (100 ≤ n ≤ 500) and large scale benchmark graphs (n ≥ 500) to obtain the near optimal chromatic number. Finding the chromatic number is an NP-hard and combinatorial optimization problem. The divide & conquer...
Cellular manufacturing system (CMS) makes use of application of group technology. The objective of cell formation problems (CFP) in CMS is to identify part families and machine cells in order to minimize the intercellular movement and to maximize the machine utilization within a cell. Previous study in CFP generally focused on maximizing grouping efficacy (GC) by minimizing exceptional elements as...
In this paper we propose a novel method to improve seam carving based on the method meta-heuristic algorithms combining simulated annealing (SA) and genetic algorithm (GA). SA is a single solution method which searches locally while GA belongs to population based algorithms that globally search to find the best answer. By this strategy, both speed and quality of the seam carving method can be increased...
This paper proposes a task mapping algorithm based on genetic algorithm for energy-efficient MPSoC design. To improve the solution quality, the proposed algorithm generates a fixed number of next population using a crossover of randomly selected elite chromosomes. In the experimental results, the proposed algorithm finds a higher quality solution which consumes lower energy while satisfying the timing...
The Pickup and Delivery Problems (PDP) represent an important class of Vehicle Routing Problems (VRP) in which goods must be collected and distributed. In this paper, we propose an approach which is based on the combination of Genetic Algorithm (GA) with the clustering algorithm for the optimization of multi-vehicles, multi-depots, pickup and delivery problem (m-MDPDP). The main contribution is to...
In this paper effectiveness of newly introduced ‘teaching learning based optimization’ (TLBO) is evaluated against different benchmark optimization problems. The effectiveness, then, is compared with the performance of genetic algorithm (GA) using the same parameters as used with TLBO. The functions on which the two algorithms applied in this work are rastrigin function, quartic, rosenbrock, six hump...
Structural testing is concerned with the internal structures of the written software. The targeted structural coverage criteria are usually based on the criticality of the application. Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that was introduced to the industry by NASA. Also, MC/DC comes either highly recommended or mandated by multiple standards, including ISO...
An adaptive genetic algorithm using mutation matrix is introduced for the solution of a series of zero/one knapsack problems of increasing complexity and structure. The evolution of the population in our adaptive genetic algorithm is based on a time dependent mutation matrix that is co-evolving, guided by the locus statistics and the fitness distribution of the population. This co-evolution of the...
We describe in this paper the Bat Algorithm and a proposed enhancement using a fuzzy system to dynamically adapt its parameter, original method is compared with the proposed method and also compared with genetic algorithm, providing a more complete analysis of the effectiveness of the bat algorithm. Simulation results on a set of mathematical functions with the fuzzy bat algorithm outperform the traditional...
Nowadays, public transportation has become an essential area for the actual society, which directly affects the quality of life. There are different sort of public transportation systems. One type that receives much attention these days because of its great social interest is the transportation on-demand. Some of the most well-known on-demand transports systems are the Demand Responsive Transit, and...
The effectiveness of combinatorial interaction testing (CIT) to test highly configurable systems has constantly motivated researchers to look out for new techniques to construct optimal covering arrays that correspond to test sets. Pair-wise testing is a combinatorial testing technique that generates a pair-wise interaction test set to test all possible combinations of each pair of input parameter...
Community structure is one of the basic characteristics of a complex network, which plays an important role in the function of a network. According to the premature convergence of traditional genetic algorithm on community detection, this paper proposes a new coding scheme based on the attribute partition of edges. The new strategy is named as NGACD. Each nonzero gene in the NGACD represents the attribute...
Aiming at the defects of Genetic Algorithm (GA) for solving the Maximum Clique Problem (MCP) in more complicated, long-running and poor generality, a fast genetic algorithm (FGA) is proposed in this paper. A new chromosome repair method on the degree, elitist selection based on random repairing, uniform crossover and inversion mutation are adopted in the new algorithm. These components can speed up...
Graph coloring problem is a classical example for NP-hard combinatorial optimization. Solution to this graph coloring problem often finds its applications to various engineering fields. This paper exhibits the robustness of genetic algorithm to solve a graph coloring. The proposed genetic algorithm employs an innovative single parent conflict gene crossover and a conflict gene mutation as its operators...
Multi parent crossover has been successfully applied to solve many combinatorial optimization problems such as unconstrained binary quadratic programming problem (UBQP). This because using more than two parents has increased the intensification process by exploiting the information shared by multi parents. However not all type of crossovers are suitable to solve vehicle routing problem (VRP). Therefore,...
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