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For several special features in the environment of cloud computing, which may be quite different from the centralized computing infrastructure currently available, the existed method of resource allocation used in the grid computing environment may not be suitable for these changes. In our paper, a new...

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, necessitating advanced diagnostic tools that provide high accuracy and efficiency. This paper introduces a novel framework, the “Gorilla Troops Optimization-based Convolutional Neural Network (GTO-CNN) for Lung Cancer...

Passenger and freight train scheduling problem on double-track railway line is considered by using Ant Colony Optimization (ACO) algorithm. The aim is to reasonably arrange the dispatch sequence of the trains to minimize the total run time. The constrains in train scheduling problem are considered and...

A mathematical model is proposed to analyse the optimization method of function chain design solution. In the approach, similarity theory is used to analyse and calculate the Generalized Distance (GD) of two adjacent components in a design solution. The evaluation criteria of sub-functions are used to...

According to the problem of dangerous objects transportation route optimization, using the colony algorithm theory as a guide, making analyses on the degree of risk road calculation model,developing ACO, then writing in MATLAB transport of dangerous objects route optimization program,and validating in...

Ant Colony Optimization algorithm (ACO) is a viable method for attacking hard combinatorial optimization problems. In this paper, researchers applied adaptive method to the Max-Min ant system (MMAS). In every cycle of the search, researchers can determine the number of elite ants adaptively. In the search...

Airborne Electronic Equipment data is unmeasurable, and computing the parameter based on component model is inaccurate and is time costing. The paper presents airborne electronic equipment parameter estimate method based on clustering by fast search and find of density peaks (CFSFDP) and ant colony optimization...

Web service composition optimization is a typical NP-hard problem to which the Ant Colony Optimization algorithm is applied appropriately for its excellent distributed computing capability and strong robustness. In this paper, we propose a new modified ant colony optimization algorithm called MACS and...

The goal of biomimicry is to resolve problems by studying and mimicking the characteristics of organisms or design elements in nature. Although wireless sensor networks are used in various fields, they have limited network lifespan. Research has thus focused on observing and modeling the behavioral principles...

Concurrent programs are being widely adopted in development of multi-core and many-core processors. However, these types of programs present some features such as concurrency, communication and synchronization which make their testing more challenging than sequential programs. Search-based techniques,...

This paper proposes enhancements to the traditional ant colony optimization (ACO) algorithm for path planning. Firstly, it improves the heuristic function by combining current step size ε and the Euclidean distance of the endpoint μ, strengthening path directionality. Secondly, it updates pheromone volatilization...

It is the most important thing to respond to mine fire that determining the optimal rescue path. This article is put forward the coefficient of accessing difficulty level by analyzing the factors which affecting underground fires, then constructing the optimal rescue path model of underground fire by...

The bus rapid transit (BRT) system is an efficient public transport mode implemented recently in many cities, but still unknown in many developing countries. The aim of this paper is to introduce the BRT concept in Cotonou by developing a new model. Based on ant colony optimization (ACO), a heuristic...

For logistics companies facing the challenges of high distribution costs and high carbon emissions when delivering fresh produce, this text comprehensively analyzes comprehensive freight cost, time-window penalty, cargo loss, and refrigeration cost with respect to the characteristics of fresh logistics...

Ant Colony Optimization(ACO) is an intelligence-optimized algorithm Which can solve a large-scale task scheduling problem in cloud computing. However, the basic ant colony algorithm used in large scale task scheduling will easily lead to low distribution efficiency. To solve this problem, this paper...

QoS (Quality of Service) constraints_based multicast routing is one of major issues in distributed multimedia on the network. An improved algorithm based CACO (Chaos Ant Colony Optimization) is proposed in this paper for solving some routing problems such as the convergence speed, packet loss rate and...

Ant colony algorithm is a typical algorithm of swarm intelligence algorithm. This article introduces the recent development of this algorithm both in principles and in applications. From the basic principle of ant colony algorithm, the paper evaluates its future development.

Path planning technology is the precondition of unmanned aerial vehicle (UAV) airspace safety. For in the running features of the UAV in 3-D space environment, putting forward using fight level (FL) guiding factor to improve the basic ant colony optimization(ACO), which improved the quality and the operation...

Targeting the structural challenges inherent in higher vocational Hotel Arabic teaching—specifically rigid curriculum sequencing, the disconnection between content supply and industry standards, and the imbalance of cognitive load—this paper proposes an Entropy-Based Adaptive Ant Colony Optimization...

Optimized task scheduling is one of the most important challenges in parallel and distributed systems. In such architectures during compile step, each program is decomposed into the smaller segments so-called tasks. Tasks of a program may be dependent; some tasks may need data generated by the others...

Considering trust issues in cloud computing, we analyze the feasibility of adopting ant colony optimization algorithm to simulate trust relationships between entities in the cloud and then propose a novel behavior trust model: ACO-BTM. Trust relationships between entities in cloud computing are dynamic,...

Fuzzy logic has been a useful tool for modeling complex problems, with the use of fuzzy variables and fuzzy rules, and in this paper we use a fuzzy system for parameter adaptation in the Ant Colony Optimization (ACO meta-heuristic). In this case we perform the dynamic adaptation of Alpha and Rho parameters;...

As we known, ants are blind and single ant’s capacity is limited. But researchers have studied that ant colonies have egregious ability to search shorter path which loads between their nests and foods. Inspired from this and based on ant colony optimization(ACO), we propose a new approach about attributes...

In the Software Development Life Cycle (SDLC), software evolution plays a crucial role in maintaining product quality, minimizing risks, and reducing the need for extensive rework. The software industry continuously seeks to enhance the quality and reliability of software products. Recent development...

In order to find the optimal scheduling, to ensure the global optimization, and to adapt to the dynamic environment, the adaptive capacity remote sensing data cloud platform scheduling strategy is proposed based on the cloud platform high score data storage model. The main contents are as follows. The...

In this paper, we attempted to find an effective method to resolve multi-satellite observation scheduling problems. Firstly, an acyclic directed graph model for multi-satellite observation scheduling was constructed. Secondly, based on the graph model, we presented a novel hybrid ant colony optimization...

Service selection problem refers to the selection of appropriate Web services from a large number of candidates in order to create complex composite services that can satisfy users’ quality-of-service (QoS) requirements. However, the existing services selection methods seldom consider the parallel...

Stochastic Traveling Salesman Problem (S-TSP) with Partial Visibility and Randomized Edge Weights is a critical challenge in disaster management where uncertainty and dynamic conditions hinder effective rescue operations. To address this, five optimization algorithms, Genetic Algorithm (GA), Ant Colony...

The enactment of Large-Scale Social Restrictions (PSBB) then changed to the Enactment of Community Activity Restrictions (PPKM) level 1, 2, 3, and 4 so that learning activities in schools are carried out online through online learning applications. This condition becomes a test for the professionalism...

Combinatorial Problems (NP hard Problem) have always been a hard task to be solved to optimal level but for the efficiency and finding the best possible solution in a certain span of time it has been solved to suboptimal level. During the study for solving the combinatorial problems to suboptimal level...

Resources scheduling plays an important role in Cloud testing. The completion time for the entire testing works in Cloud testing and the cost of Cloud services could both reduce a lot through good scheduling strategies. This paper mainly focuses on the dependencies between testing tasks and proposes...

Ant colony optimization (ACO) takes inspiration from the foraging behaviour of real ant species. This ACO exploits a similar mechanism for solving optimization problems for the various engineering field of study. Many successful implementations using ACO are now available in many applications. This paper...

The garment industry holds a paramount position within the Vietnamese economy. However, global industries, due to the aftermath of economic recessions and the impacts of epidemics, have faced imperatives to curtail expenses and optimize operational processes to bolster competitiveness. In this context,...

An ACO-PSO Hybrid Algorithm Solving Path Planning Problem based on Swarm Intelligence(SI) is proposed. The problem first is described and some corresponding definitions are presented. Ant colony optimization (ACO) is used to establish the corresponding solution, and some material algorithm steps are...

Task scheduling in cloud computing environments is crucial for optimizing resource allocation and enhancing system efficiency. In this paper, we present a systematic analysis environment for evaluating various task scheduling algorithms. We focus on three prominent algorithms: Ant Colony Optimization...

This paper proposes the combination of Swarm Intelligence algorithm of artificial bee colony with heuristic scheduling algorithm, called Heuristic Task Scheduling with Artificial Bee Colony (HABC). This algorithm is applied to improve virtual machines scheduling solution for cloud computing within homogeneous...

DNA computing research in the last 20 years has attracted the attention of many researchers from various scientific disciplines. Many researchers have succeeded in demonstrating the ability of bio-molecules DNA computing to be used as storage media and biochemical tools as information processing operators....

In this study, the software releasing planning (SRP) problem resulted from incremental software development is considered. Software releasing planning has been proven to be a NP-complete problem. Owing to the intractable nature of the problem, a heuristic approach based on ant colony optimization (ACO)...

The need for bioethanol each year increases steadily while raw materials tend to decline, this is due to bioethanol raw materials, so sought after materials that can be regenerated, bamboo is one of the alternative raw materials, Bamboo has a cellulose content ranging from 42.4%-53.6%. The chemical process...

The research of UAVs(Unmanned Aerial Vehicle) has received a lot of attention in recent years, and more and more UAV manufacturers have emerged in China and abroad, such as DJI, 3D Robotics, Parrot and so on. The advantage of UAVs over manned vehicles is that they can perform missions in dangerous and...

Path planning constitutes one of the fundamental technologies in robotic navigation. Focusing on the operational environment of wheel-legged lunar rovers on the actual lunar surface, this paper proposes and establishes a novel integrated planning methodology based on fuzzy control theory and ant colony...

Previous research has attempted to integrate the ethical aspect of responsible leadership and the strategic aspect of responsible leadership (RL) by formulating a multidimensional measurement. This study aims to further explore the multidimensional measurement of responsible leadership by examining its...

Underwater Sensor Networks (USNs) are increasingly vulnerable to malicious node attacks, compromising data integrity and network performance. Inspired by the remarkable camouflage capabilities of stonefish, we propose a novel malicious node detection and data aggregation scheme for USNs, leveraging the...

In this paper, a novel ant colony optimization (ACO) simulation platform is developed by MATLAB/GUI toolbox to solve traveling salesman problem (TSP). The modular design concept is applied to divide platform into four main modules. The function modules are designed by using MATLAB/GUI toolbox. The development,...

In order to deal with low efficiency and accuracy of detection caused by the improper selection of Xgboost parameters in Android malware detection. In this paper, we introduce Ant Colony Optimization (ACO) into Xgboost parameters optimization and propose an approach based on ACO optimize Xgboost parameters...

This paper presents an hybrid algorithm based on genetic algorithm and ant colony optimization for continuous optimization, which combines the global exploration ability of the former with the local exploiting ability of the later. The proposed algorithm is evaluated on several benchmark functions. The...

Ant colony algorithm is often used to solve the IP traceback problem without the entire network routing information. However, such algorithm is easy to converge to a local suboptimal solution. Especially with the increase of network topology size, the real attacker is more difficult to find. In this...

The parameters of the modified mixed Ant Colony Optimization (ACO) - k-means image segmentation algorithm are considered. There have been investigated such parameters as n - the number of ants; heuristic coefficients of ACO algorithm and their dependence on the image scale and number of iterations before...

Accurate brushless DC motor position control is the basis for realizing various high-precision control systems. In order to achieve precise control of brushless DC motor position and improve control stability, this paper proposes a fuzzy PD control method based on the improved ant colony optimization...

The This study aims to determine the impact of democratic public space presented by representatives of the people to constituents in terms of character development and the maturation of citizens’ understanding of democracy. Democracy and citizenship cannot be separated as the main principles of a democratic...