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The location problem of logistics center is the key process of logistics distribution, in order to improve the accuracy of the location of logistics center, this paper according to the parallelism and characteristics of global optimization of genetic algorithm. A method based on genetic algorithm is proposed to solve the problem of logistics center location, and set up with the minimum total cost...
Most published results show that power reduction of the finite-state machines (FSMs) is achieved by decomposition. In order to achieve a low power FSM implementation, a Genetic Fuzzy c-mean clustering-based decomposition method, called GFCM-D, is proposed for FSM partition in this study. GFCM-D used Fuzzy c-mean clustering (FCM) to partition a set of states of FSM into a collection of c fuzzy clusters,...
Efficient design of networks topologies is challenging, especially with the arrival of the virtualization in these last years. In this paper, we deal with the Capacitated Network Design Problem (CNDP) with modular link capacities to design minimum cost network while satisfying the flow demands. We propose a two levels Genetic Algorithm (GA) based model that can deal with several variations of CNDP...
Selecting runtime parameters while applying Genetic Algorithm is a crucial decision. Numerous theoretical and empirical researches are performed and guidelines are suggested on this, researches are conducted but still an overall acceptable guideline is lacking. In this work the parameters are discussed with reference to the existing literature and suggested a guideline to follow for initial setup...
This paper deals with a class of interval linear bilevel programming problems, in which some or all of the leader's and follower's objective function coefficients are specified in terms of intervals. The focus of solving this class of problems is on determining the optimal value range when different coefficients of objectives are taken in intervals given. In order to obtain the best and the worst...
Increased penetration of distributed generators (DGs) is one of the characteristics of smart grids. Distribution grid reconfiguration is one of the methods of accommodating more DG into the electric grid, which is illustrated with the help of a 16 node test network in this paper. The reconfiguration of the distribution grid involves changing the grid topology thereby optimizing a few objectives. In...
This paper proposes a service restoration algorithm considered with priority customers and Distributed Generation (DG). By establishing an index of service restoration rate considering load grade, the power supply to the priority customers is ensured. Taking advantage of DG with regard to the service restoration in distribution networks, when the grid does not have enough capacity to restore the entire...
This paper presents a hybrid multi-chromosome genetic algorithm (HMCGA) to solve an in integer linear programming formulation of the Cutting Stock Problem (CSP). The CSP is an important class combinatorial problem. It is appropriate to minimize the raw material used by industries for fulfilling customer's demands. In such cases, classic models for solving the cutting stock problem are useless. HMCGA...
TSP is a well-known NP-hard problem. Although many algorithms for solving TSP, such as linear programming, dynamic programming, genetic algorithm, anneal algorithm, and ACO algorithm have been proven to be effective, they are not so suitable for the more complicated large scale TSP. This paper offers a method to decompose the large-scale data into several small-scale data sets by its relativity; and...
From the procedure how a locksmith match a key to a lock, a new algorithm called the "key-cutting algorithm" is introduced. There are so many existing algorithms for solving the optimization problem like genetic algorithm, linear programming and the artificial immune algorithm. For any problem these algorithms would apply, so does the key-cutting algorithm. At the same time, some already...
For nonlinear bi-level programming problems in which the follower's problem is linear, the paper develops a genetic algorithm based on a mixed encoding technique. At first, each individual consists of two parts, the first part is the leader's variable values using real-encoding, whereas the second one is the sequence number of basic variables of the follower's programming, which are some integers...
In this paper, a novel genetic programming named linear genetic programming with reusable gene (LGPRG) has been proposed. This new method absorbed the merits of many other linear genetic programming. It codes with a simple, nearly unrestrained string. Based on its character of reused, more expressions could be contained in one chromosome without the increase of computation task.Further more, the expression...
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