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This paper presents an efficient method for the reconfiguration of radial distribution systems for minimization of real power loss using adapted ant colony optimization. The conventional ant colony optimization is adapted by graph theory to always create feasible radial topologies during the whole evolutionary process. This avoids tedious mesh check and hence reduces the computational burden. The...
An optimization model for tree-type pipe network is established, in which the minimal investment is taken as objective function. The improved integer coding genetic algorithm is designed to optimize the model, through the coding mode design, the optimizations of pipe network layout and pipe diameter are achieved simultaneously, and the pipe diameter restriction is satisfied automatically. In the algorithm...
In order to ensure every feasible assembly sequence is included in the searching space of genetic algorithm, this paper proposes an improved genetic encoding method. In this method, every chromosome is encoded by a permutation of integer. Although the final form of chromosome is the same as the existing form, the decoding process is different. In our decoding process, every permutation of integer...
This paper examines the applicability of the genetic algorithm (GA) to generation of nonbinary low-density parity-check (LDPC) codes over GF(q) which is suitable for distributed video coding (DVC). Error probability distribution in side-information of the DVC is approximated by Gaussian and Laplace distributions, and then a fitness of an LDPC matrix is defined under this approximation. The GA is designed...
To find MST (Minimum Spanning Trees) in complete graph is a classical problem in operation research having network design as an important application. It is possible to solve MST problem efficiently, but its Biobjective versions are NP hard. In this paper, we present a comparison of two encoding schemes for representing tree in Biobjective optimization scenario. The three different instances of Biobjective...
In recent years, with the massive use of Golomb rulers in various fields of engineering, new optimal rulers have become an important subject of search. Many different approaches have been proposed to tackle the Golomb ruler problem such as exact methods, constraint programming, local searches and evolutionary algorithms. This paper describes an hybrid evolutionary algorithm to find optimal or near-optimal...
In this paper, Genetic algorithms is applied to traveling salesman problem whose solution requires encoding of real values in DNA strands. Encode weights in DNA computing is an important but challenging problem because many practical applications in the real world involve weights. In order to efficiently encode weights in DNA strands, we firstly proposed two definitions, the order number of weight...
This paper presented a novel approach to search and optimize path points for anti-ship missile path planning. We utilized the method of MAKLINK graph to construct free space, and then, a global state connected graph is built up for searching for all possible routes. genetic algorithm is used to search and optimize path points severally in these local routes. According to flight rules and technique...
The multi-source network coding problem, in which multiple multicast sessions with independent data share a network, is an open challenge. This paper proposes an approach to implement multi-source multicast sessions with linear network coding. We divide the original network into several sub-graphs, and each sub-graph contains a source node and its corresponding sink nodes. Links belonging to different...
Using traditional genetic algorithm (GA) to solve distribution network reconfiguration, the required radial network structure can not be ensured and a large number of infeasible solutions are brought about. Although some improved methods were put forward, they either are of computational complexity or can not completely settle the problem. In this paper, the strategy of searching randomly spanning...
MTSP included two categories: the first, distributed visit cities (points) number to every salesman, the distribution required balanced cities number. Second distributed MTSP walking distance to every salesman, it required balanced path length. For the MTSP which balance route, designed the hybrid algorithm, it based on genetic algorithms and 2-opt algorithm. The coding method, algorithm steps and...
The multi-objective degree-constrained minimum spanning tree problem (MST) is an NP-hard problem. In this paper, a model of the problem is formulated and an improved genetic algorithm for the problem is proposed. We employ partheno-genetic operations to improve the efficiency of genetic algorithm, and design a niche count with adaptive niche radius to keep the population diversity. The experiments...
Bayesian networks encode causal relations between variables using probability and graph theory. We employ genetic algorithm to exploit these causal relations from data for classification problems, thus restricting the search space from directed acyclic graphs to trees. Prufer number encoding of the structure is employed for the representation of individuals in the genetic algorithm. Several score...
The critical issue in designing correlated data networks like Wireless Sensor Networks is to minimize the total cost of data transmission in the network, and decrease the amount of data flow. The problem of finding optimal aggregation tree for correlated data gathering in single sink network is considered as an NP-Complete problem and hence heuristic methods are usually applied to solve it [1]. In...
Generating economical single-product flow-line configurations as candidates for a given demand period is a key optimization problem for reconfigurable manufacturing systems (RMS) at both initial design and reconfiguration stages. The optimization problem addresses the questions of selecting number of workstations, number and type of machines as well as assigned operations for each workstation. Given...
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