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In this study, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a single depot and identical vehicles, is considered. Minimizing the total distance and the total waiting time of the vehicles are determined as objective functions for VRPTW which is capable to serve the customers in a prespecified time interval. A hybridized version of genetic algorithm which is a metaheuristic...
In this paper, an adaptive genetic algorithm based on multi-population elite selection strategy is proposed. The multi-population elite selection strategy is used to preserve the optimal individuals of each group. Finally, these optimal individuals formed a population, and then use the improved adaptive genetic algorithm to finish the solution. By comparing the simulation experiments of TSP problem...
In this paper, we present a new method based on the genetic algorithm (GA) and the weighted sum method (WSM) for aligning RNA sequences. This new approach has been developed in two steps. First, we have developed a multi-objective optimization algorithm using three objective functions: Entropy, Weighted Fully Matched Column (WFMC), and the Base Pair Score (BPS) [1]. Subsequently, the WSM was used...
There is a necessity to schedule the system and user processes by the operating system to getting maximum utilization of the CPU and obtaining high throughput. This paper presents a dynamic scheduling algorithm that make use of genetic algorithm operations for scheduling multi non-preemptive task on uniprocessor system to get minimum average waiting time and average turnaround time. The algorithm...
Swarm intelligence systems are basically made up simple agent's populations which are interacting locally with each other and with their surroundings. These agents local interaction with each other can be negative, positive or neutral. Here positive interaction helps agents to solve a problem while negative interaction block the agents for solving problem. swarm's performance does not affected by...
The analysis of communities and their evolution in dynamic networks is a challenging research with broad applications. The recent studies have found that the overlaps between communities are more densely connected than the non-overlapping parts in some real networks. The findings are different from the present concepts of the overlapping communities. Existing methods may fail to detect this kind of...
Nowadays, nesting problem has been encountered in many manufacturing industry. Nesting problem is given lots of layout elements and using algorithm to looking for the most suitable positions of every layout element in template to save the resource. In this paper, the two-dimensional problem is considered. The width of template is assumed to be fixed, and the heuristic and genetic algorithm is used...
Today, Cognitive radio (CR) is found to be the key technology to exploit the unused available spectrum resources; it can sense and use spectrum in an opportunistic manner without creating any harm to cognitive users. In this paper, we develop a cognitive radio access strategy based on the implementation of a dynamic genetic algorithm for CR. The crossover and mutation operators are developed to keep...
Differential Evolution algorithm has recently emerged as a simple yet very powerful technique for real parameter optimization. This article describes an application of DE for the design of fractional order proportional Integral Derivative controller. FOPID controller parameter are composed of the proportional constant, integral constant, derivative constant, derivative order and integer order, and...
The problem of dynamic stochastic shortest path is NP-hard. The transportation network of the city is dynamic and stochastic, the optimal problem of path is widely used in the fields of transportation, communication and computer network. The paper investigates the shortest path problem based on the genetic algorithm principle, an improved self adaptive genetic algorithm is proposed by encoding the...
Amid the most widely studied NP-hard combinatorial optimization problems, the Probabilistic Traveling Salesman Problem (PTSP), which is an extension of the well-known Traveling Salesman Problem, offers a fundamental basis for analyzing the stochastic impacts in routing problems. In this paper, a new meta-heuristic approach, Genetic Minimum Matrix Search (GMMS), is introduced for the solution of the...
Feature subset selection is an important research branch in the field of pattern recognition. Due to the traditional feature selection algorithms do not take into account the feature updating case, the paper analyzes the relationship between dataset and features, proposes a new feature activity measurement that is used to determine the influence among different features on some certain conditions...
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 work presents a method for solving optimal number and location of power quality monitors in transmission power systems. The problem is modeled as a multi-objective problem to acquire a tradeoff between the data redundancy and the economical efficiency. A multi-objective optimal placement model is built, in which the monitoring locations and the number of monitors are taken as objects. Adaptive...
The PDPTW (Pickup and delivery problem with Time Windows) is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. In this paper, we present an approach based on genetic algorithm, aggregation method and minimum values for optimization of the dynamic multi-pickup and delivery problem with...
Software reuse is one of the major research area in component based software engineering (CBSE). It is an area which integrates all the other technical areas like data mining, soft computing, artificial intelligence etc. The major areas which are to be focused in software reuse are classification, clustering, searching, indexing and retrieval of software components. There are many techniques described...
We describe in this paper the Bat Algorithm and a proposed enhancement using a fuzzy system to dynamically adapt its parameter. The original method is compared with the proposed method and also compared with the 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...
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...
This manuscript proposes a hyper-heuristic approach towards mitigating Premature Convergence caused by objective fitness in Genetic Programming (GP). The objective fitness function used in standard GP has the potential to profoundly exacerbate Premature Convergence in the algorithm. Accordingly several alternative fitness measures have been proposed in GP literature. These alternative fitness measures...
Metaheuristics algorithms show very good performance in solving various job scheduling problems in computational grid systems. However, due to the complexity and heterogeneous nature of resources in grid computing, stand-alone algorithm is not capable to find a good quality solution in reasonable time. This study proposes a hybrid algorithm, specifically ant colony system and genetic algorithm to...
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