Max-Min Ant Colony Algorithm Research Articles

Research on Improvement of Hotel Supply Chain Resource Management Decision in the Era of Big Data

Hotel supply chain management (SCM) refers to the material service that takes a hotel as the core object. At present, the main method is centralized SCM, which uses integer programming or mixed integer programming to establish and solve the allocation management of various resources among hotels in the supply chain. In this article, based on ant colony algorithm (ACA), the hotel SCM mode is studied and optimized. The research shows that the convergence path is A-S4-M3-L3-D1-R1-T. Therefore, the optimal partner combination meeting the requirements of the supply chain is S4, M3, L3, D1 and R1. The experiment shows that the max-min ACA is effective to solve the problem of partner selection in hotel supply chain. By using enterprise management technology, information technology, network technology and SCM technology under ACA, the effective rules and control of information flow, logistics, capital flow, business flow and value flow in the whole supply chain can be achieved, and the maximum benefit of the whole hotel supply chain can be realized.

Route optimization of hazardous freight transportation in a rail-truck transportation network considering road traffic restriction

With the increasing demand for chemical products in China, how to manage the risks associated with hazardous freight transportation has attracted arising attentions from both government and industry practitioners. From the perspective of carrier companies, transportation modal choice and routing for hazardous freight transportation need to be carefully designed, which motivates current research. This paper aims to optimize the service mode and routing for hazardous freight transportation in a rail-truck network with bi-objectives optimization approach. Several practical concerns are addressed, including the coordination of rail transportation which has fixed train running plan and road transportation which is flexible and mobile, and the consideration of alternative path when the expressway is temporally blocked for hazardous freight due to the traffic restriction measurements on inter-city road segments. Furthermore, the time-varying transportation risks and costs associated with accidents of hazardous freight transportation are investigated. The Max-Min Ant-colony Algorithm (MMAS) algorithm is adopted for solution. For model validations and conclusion generalization, this paper implements a real-life case study in Beijing-Tianjin-Hebei region in China with the objective of minimizing transportation risks and costs. The solutions show that traffic restrictions have an adverse impact on the carrier and alternative paths are able to help the carriers further optimize their routing strategy. A careful consideration and appropriate processing of differences in operational characteristics of two transportation modes, is able to provide a better and more realistic understanding of rail-truck hazardous freight transportation problem.

Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm

As a result of the green IoT, application layer users are increasingly seeking more services, and it is particularly important to reduce the energy consumption of an IoT monitoring center while ensuring service reliability. In this paper, the max-min ant colony algorithm is proposed to effectively solve the problems of user service reliability and energy consumption optimization of an IoT monitoring center. First, the service reliability of the application layer users is modeled based on a Markov chain, and the quantitative reliability performance indicators are given. Second, an optimization model between the user service reliability and the energy consumption of an IoT monitoring center is established. Finally, the optimization problem is solved based on the improved max-min ant system. Simulation experimental results show that compared with the improved FFD algorithm, the average power consumption of the max-min ant colony algorithm can be reduced by up to 7.14%.

A Quantum MMAS Based Algorithm for Multicast Routing Problem

For solving the problem of multicast routing, ant colony algorithm (ACO) has insufficient optimization ability. The paper proposes a routing algorithm which combines quantum computing and max min ACO. The algorithm uses quantum bit probability amplitude to encode the link, and dynamically adjusts quantum revolving gate to update the quantum coding on the link, so as to meet the cost optimization under constraint conditions, combined with the maximum and minimum pheromone decision mechanism to find the optimal link path, effectively control the evolution speed and direction, and enhance the convergence performance of the algorithm. The simulation results show that the algorithm can effectively control the evolution speed and direction, and is better than ant colony algorithm in the optimization ability and convergence performance.

Quantum Max-min Ant Colony Algorithm For QoS Routing Problem

Aiming at the ant colony algorithm is weak to solve the problem of QoS routing, this paper proposes a routing algorithm that combines quantum computing with the max-min ant colony algorithm. The algorithm introduces a quantum selection strategy, uses qubit probability amplitude to encode the path, and dynamically adjusts the quantum rotation gate to update the path quantum coding on the basis of the minimum cost to meet the constraints and other optimal conditions, combined with the maximum and minimum pheromone determination mechanism to find the optimal path, effectively control the evolution speed and direction, and accelerate the algorithm convergence. Experimental results show that the algorithm is effective in controlling the speed and direction of evolution, and has better optimization ability and convergence performance than ant colony algorithm.

Load Distribution Optimization Based on Max-Min Ant Colony Algorithm in Hot Strip Rolling Process

A reasonable allocation of load distribution is expected when the full capacity of rolling equipment is exerted, and energy conservation and strip quality requirements are satisfied. In this work, the minimum value of the mill consumptive power summation and the optimum of the mill shape are used as the target function. Based on equipment parameters of a national hot strip rolling mill, a load distribution optimization method (subjected to certain constraints) was applied and a Max-Min ant-colony algorithm was subsequently used to optimize the load distribution of the mill. The optimization value was determined from the optimal path chosen by ants, and the optimum load distribution was obtained after a series of iterations. The compression ratio from upstream stands to downstream stands decreased gradually after optimization by this method, and the proportional crowns varied less than those associated with the traditional energy method. In fact, the amplitude of fluctuation was reduced by nearly 50%, which is favorable for strip shape controlling, and the total dissipative power was lower than that of the energy consumption method. Moreover, the overall power can be reduced by 4.19%, and an optimal rolling load distribution of the hot strip rolling process can be obtained.

A Dynamic Edge Exchanged Ant Colony Algorithm for TSP Problem

Aimed at solving premature convergence and low speed in heuristic algorithms for TSP problems, this paper analyzed the principle of Max-Min Ant colony algorithm (MMAS) and Lin-Kernighan algorithm, then proposed a dynamic exchange of Max-Min Ant colony algorithm (MMAS-LK). The new algorithm used MMAS to initially a set of the solutions in the early state, then utilized the improved Lin-Kernighan algorithm for local optimization, and dynamic adjustment parameters according to the process of computing avoid falling into local optimum. The simulation results showed that the proposed algorithm compared with the original MMAS and Lin-Kernighan algorithm, it has a better speed and precision in the TSP problem.

A Vehicle Routing Optimization Method with Constraints Condition based on Max-Min Ant Colony Algorithm

According to the command quantity of customers and limits of distribution vehicle, in order to obtain more profit, optimization study on vehicle routing and quantity is needed. Basic ant colony algorithm has slow convergence speed and is easy to falling into local optimum when used to solve this problem, while max-min ant colony algorithm can overcome these shortcomings and is the best algorithm to solve this problem at present. In this paper, vehicle routing optimization on constraints condition is simulated with max-min ant colony algorithm on MATLAB, and the direction of vehicle routing and the least number of vehicle can be obtained from the simulation results.

Optimization Approach for Evacuation Route of Railway Freight Transportation Based on MMAS

On the background of railway freight transportation under emergency situations, the optimal evacuation function to minimize the total evacuation time and evacuation distance is put forward; in consideration of the dynamic and complex natures of evacuation network, searching evacuation route algorithm based on MMAS (Max-min ant colony algorithm) was proposed which can meet the dynamic change of evacuation network.

基于蚁群算法的PCB组装过程优化<br>PCB Assembly Optimization Based on Ant Colony Algorithm

在转塔式贴片机的印制电路板(PCB)组装过程中，元件贴装顺序和装载有不同类型元件的供料器在供料架上的布置是影响转塔式贴片机贴装时间的主要因素。在分析实际工程应用的基础上，建立了转塔式贴片机上PCB组装的集成优化模型，对蚁群算法进行了改进，提出了相互通信的最大–最小蚂蚁算法，用两种不同职能的蚂蚁相互协作，以元件组装顺序来驱动供料器布置，引导蚂蚁实现元件贴装顺序的优化，而执行蚂蚁根据引导蚂蚁选择元件的结果来实现供料器布置优化。算法可对元件贴装顺序和供料器的布置进行同时优化，从而提高转塔式贴片机上PCB组装的效率。最后通过实例验证了算法的有效性。 The component placement sequence and feeder arrangement are the critical factors determining assembly time of chip shooter (CS) machine. In addition, the different size of component and different arrangement strategy affect the feeder arrangement and component placement sequence. Based on the engineering analysis, an integrated optimization model of printed circuit board (PCB) assembly for CS machine is established. According to the parallel placement character of CS machine, “Max-Min Ant Colony Algorithm with Communication function” is designed based on traditional Ant Colony Algorithm. The idea that two ants with different duties collaborate to solve the optimization problem is presented. Guide ants optimize placement sequence while executant ants optimize feeder arrangement according to the components placement sequence. The component placement sequence and feeder arrangement are optimized simultaneously.

Optimizing the Performance of Chip Shooter Machine Based on Ant Colony Algorithm

The component placement sequence and feeder arrangement are two critical factors determining the assembly time of chip-shooter machine (CS). In addition, the different size of component and different arrangement strategy affect the feeder arrangement and component placement sequence. Based on the engineering analysis, an integrated optimization model of printed circuit board (PCB) assembly for CS machine is established. According to the parallel placement character of CS machine, "Max-Min Ant Colony Algorithm with Communication function (MMAC)" is designed based on traditional Ant Colony Algorithm. The idea that two ants with different duties collaborate to solve the optimization problem is presented. Guide ants optimize placement sequence while executant ants optimize feeder arrangement according to the components placement sequence. The component placement sequence and feeder arrangement are optimized simultaneously

Hybrid optimization model and its application in prediction of gas emission

According to the complex nonlinear relationship between gas emission and its effect factors, and the shortcomings that basic colony algorithm is slow, prone to early maturity and stagnation during the search, we introduced a hybrid optimization strategy into a max-min ant colony algorithm, then use this improved ant colony algorithm to estimate the scope of RBF network parameters. According to the amount of pheromone of discrete points, the authors obtained from the interval of network parameters, ants optimize network parameters. Finally, local spatial expansion is introduced to get further optimization of the network. Therefore, we obtain a better time efficiency and solution efficiency optimization model called hybrid improved max-min ant system (HI-MMAS). Simulation experiments, using these theory to predict the gas emission from the working face, show that the proposed method have high prediction feasibility and it is an effective method to predict gas emission.

The Research on VRP Based on Max-Min Ant Colony Algorithm

Vehicle routing problem (VRP) is the key to reducing the cost of logistics, and also an NP-hard problem. Ant colony algorithm is a very effective method to solve the VRP, but it is easy to fall into local optimum and has a long search time. In order to overcome its shortcomings, max-min ant colony algorithm is adopted in this paper, and its simulation system is designed in GUI of MATLAB7.0. The results show that the vehicle routing problem can well achieves the optimization of VRP by accessing the simulation data of database.