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A modern web service or the Internet of Things (IoT) based service is composed of various loosely-coupled service components, called microservices, running on the cloud resource. It enables that the number of active servers be adjusted following the load fluctuation, so an efficient cloud resource allocation is required. This situation is modeled as variable-sized dynamic bin packing problem where...
In recent years, there has been growing interest in learning to rank. We considered the current state of learning to rank in information retrieval systems. We proposed an approach for learning to rank problem based on multi-criteria optimization using the method of Pareto optimization and Genetic Algorithms. The performance of the method has been investigated on test data collections, also a comparison...
The main task of modern electric networks is the reliability of electricity supply to consumers, as well as in optimizing voltage levels. One of the possible measures to increase reliability is the construction of a rational topology of the electrical network and the use of distributed generation in the form of alternative sources of electricity. Such networks allow you to dynamically adjust the parameters...
Mobile edge computing (MEC) has recently emerged as an important paradigm to bring computation and cache resources to the edge of core networks. However, the resources of edge network are relatively limited, so it is necessary to cooperate with data center (DC) which has sufficient computational resources. In this paper, we aim at designing a computation offloading and data caching model under the...
In this paper, a new type of TSP, i.e. PTSP (Polymorphic Traveling Salesman Problem) is proposed. The problem is discovered from the research of scan field route optimization. As for PTSP, every node is polymorphic, which means each node can have several states, but obtains only a determined state in a determined loop, moreover a path which connects a pair of nodes can be different and have different...
The multidimensional assignment problem (MAP) is a natural extension of the well known assignment problem. A problem with s dimensions is called a SAP. The most studied NP-hard case of the MAP is the 3AP. Memetic algorithms have been proven to be the most effective technique to solve MAP. The use of powerful local search heuristics in combination with a genetic algorithm, even if it has a simple structure,...
Existing clustering techniques primarily rely on prior knowledge about the data, such as the number of clusters and radii. However, in real applications, the number of clusters and the radii of clusters are usually unknown. Therefore, the performance of clustering methods with overlapping data is degraded due to their limitations in finding all cluster centers with uneven density values. Hence, a...
This paper address the problem of scheduling a set of jobs with non-zero ready times and incompatible job families on a set of identical parallel batch machines so as to minimize the total weighted tardiness. In this problem, each machine can process several jobs of a same family simultaneously as a batch as long as the machine capacity is not exceeded. Jobs of a family has the same processing time...
The Artificial Bee Colony (ABC) algorithm is a swarm intelligence approach which has initially been proposed to solve optimization of mathematical test functions with a unique neighbourhood search mechanism. However, this neighbourhood search mechanism could not be directly applied to combinatorial discrete optimization problems. The employed and onlooker bees need to be equipped with problem-specific...
This work aims to minimize average delay for signalized traffic network along Jalan UMS under oversaturated condition using decentralized genetic algorithm (DGA). Relieving traffic network is a key challenge for a nation for improving its socio-economic systems and welfare to society. Control the traffic signal timing becomes a cost effective solution to reduce congestion since the space constraint...
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...
Tourists sometimes can only experience part of the scenic spots due to time limitation. Thus, these spots should be chosen and a path needs to be found for the tourists. However, the Particle Swarm Optimization (PSO) is on a fixed dimension and it cannot meet the above requirements. Therefore, in this paper we propose the Variable Dimension PSO (VDPSO) to plan the path. The traditional updating methods...
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...
The goal of weapon target assignment (WTA), which is one of the classic military operational problems, is to determine the best assignment scheme in order to gain the most benefit while satisfying a number of constraints deriving from the capability of available platforms and munitions (or weapons), as well as target characteristics. In order to overcome the drawbacks of premature convergence of exiting...
This paper presents algorithm for optimal reconfiguration of distribution networks using hybrid heuristic genetic algorithm. Improvements introduced in this approach make it suitable for real-life networks with realistic degree of complexity and network size. The algorithm introduces several improvements related to the generation of initial set of possible solutions as well as crossover and mutation...
The increasing tendency of container vessel enlargement and the container transportation growth, make people pay more and more attention to the efficiency of the container terminal berths. In order to improve the berth efficiency, this paper focuses on continuous berth allocation problem. Firstly, a penalty cost function is suggested to comprehensively consider the delay of vessel leaving time and...
Based on the biological mechanism of immune algorithm, an improved immune genetic algorithm is proposed, in which particle swarm optimization is taken as global searching strategy to improve the global search ability of the immune genetic algorithm, and progressive optimization algorithm is used for evolving operation of control strategy to improve its local search ability. At the same time, because...
Graph filters, which are considered as the workhorses of graph signal analysis in the emerging field of signal processing on graphs, are useful for many applications such as distributed estimation in wireless sensor networks. Many of these tasks are based on basic distributed operators such as consensus, which are carried out by sensor devices under limited energy supply. To cope with the energy constraints,...
Task scheduling is critical for obtaining a high performance schedule in heterogeneous computing systems (HCS) and searching an optimal scheduling solution has been shown to be NP-complete. In this paper, a hybrid heuristicgenetic algorithm with adaptive parameter (HGAAP) is proposed by combining a heuristic scheduling algorithm and a genetic algorithm. An existing common heuristic scheduling algorithm...
In this paper, A solution is proposed for the multi-robot task assignment in obstacle environment, which combines the A∗ algorithm with the genetic algorithm. Our main work are twofold:(a) Path planning method based on A∗ algorithm to search an optimal path between any robot and any target or any two targets; and (b) task assignment method based on the genetic algorithm for the assignment of robots...
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