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排序方式: 共有4409条查询结果,搜索用时 15 毫秒
1.
In most research on the hot strip mill production scheduling problem (HSMPSP) arising in the steel industry, it is accepted that a schedule with lower penalty caused by jumps of width, hardness, and gauge will result in lower roller wear, so it is regarded as a better schedule. However, based on the analysis of production processes, it is realised that rolling each coil also cause roller wear. In order to assessing the roller wear associated with production scheduling more precisely, it is necessary to consider it as another factor besides those jumps, especially when complicated constraints are involved. In this paper, an improved method is proposed to quantify the expected wear of the rollers done by those jumps and rolling processes. Then the HSMPSP whose objective is to maximise the total length of all scheduled coils is formulated as a team orienteering problem with time windows and additional production constraints. A heuristic method combining an improved Ant Colony Extended algorithm with local search procedures dedicated to HSMPSP is developed. Finally, computational results on instances generated based on production data from an integrated steel mill in China indicate that the proposed algorithm is a promising solution specific to HSMPSP. 相似文献
2.
针对多目标绿色柔性作业车间调度问题(MGFJSP)的特点,提出从碳排放量、噪声和废弃物这3个指标来综合评定环境污染程度,建立了以最小化最大完成时间和环境污染程度为优化目标的MGFJSP模型,并提出了一种改进的人工蜂群算法来求解该模型。算法的具体改进包括:设计了一种三维向量的编码和对应解码方案,在跟随蜂搜索阶段引入一种有效的动态邻域搜索操作来提高算法的局部搜索能力,在侦查蜂阶段提出产生新食物源的策略用于增加种群的多样性。最后进行了实验研究与算法对比,以验证所建模型和所提算法的有效性。 相似文献
3.
Here a new model of Traveling Salesman Problem (TSP) with uncertain parameters is formulated and solved using a hybrid algorithm. For this TSP, there are some fixed number of cities and the costs and time durations for traveling from one city to another are known. Here a Traveling Salesman (TS) visits and spends some time in each city for selling the company’s product. The return and expenditure at each city are dependent on the time spent by the TS at that city and these are given in functional forms of t. The total time limit for the entire tour is fixed and known. Now, the problem for the TS is to identify a tour program and also to determine the stay time at each city so that total profit out of the system is maximum. Here the model is solved by a hybrid method combining the Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The problem is divided into two subproblems where ACO and PSO are used successively iteratively in a generation using one’s result for the other. Numerical experiments are performed to illustrate the models. Some behavioral studies of the models and convergences of the proposed hybrid algorithm with respect to iteration numbers and cost matrix sizes are presented. 相似文献
4.
Multi Compartment Vehicle Routing Problem is an extension of the classical Capacitated Vehicle Routing Problem where different products are transported together in one vehicle with multiple compartments. Products are stored in different compartments because they cannot be mixed together due to differences in their individual characteristics. The problem is encountered in many industries such as delivery of food and grocery, garbage collection, marine vessels, etc. We propose a hybridized algorithm which combines local search with an existent ant colony algorithm to solve the problem. Computational experiments are performed on new generated benchmark problem instances. An existing ant colony algorithm and the proposed hybridized ant colony algorithm are compared. It was found that the proposed ant colony algorithm gives better results as compared to the existing ant colony algorithm. 相似文献
5.
Krishnasamy Ragavan Krishnan Venkatalakshmi Kandasamy Vijayalakshmi 《Computational Intelligence》2021,37(1):538-558
Road traffic congestion is a serious problem in today's world and it happens because of urbanization and population growth. The traffic reduces the transport efficiency in the city, increases the waiting time and travel time, and also increases the usage of fuel and air pollution. To overcome these issues this papers propose an intelligent traffic control system using the Internet of Vehicles (IoV). The vehicles or nodes present in the IoV can communicate between themselves. This technique helps in determining the traffic intensity and the best route to reach the destination. The area of study used in this paper is Vellore city in Tamilnadu, India. The city map is separated into many segments of equal size and Ant Colony Algorithm (AOC) is applied to the separated maps to find the optimal route to reach the destination. Further, Support Vector Machine (SVM) is used to calculate the traffic density and to model the heavy traffic. The proposed algorithm performs better in finding the optimal route when compared to that of the existing path selection algorithms. From the results, it is evident that the proposed IoV‐based route selection method provides better performance. 相似文献
6.
针对成品油二次配送路径优化问题,提出了一种可变成本与动态载荷相关的评价指标。考虑蚁群算法求解路径优化问题的高效性,设计了一种等级反馈蚁群(HFAC)算法。采用局部距离等级策略代替基本蚁群算法的随机选取;利用较优(较差)个体对其所在路线进行正(负)反馈调整信息素浓度;对最优路线的子路线进行末端优化调整。通过15组不同类型算例进行仿真实验表明,HFAC算法在成品油二次配送路径优化中优于基本蚁群算法。 相似文献
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8.
Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach. 相似文献
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10.
针对当前空间规划方法存在的计算时间长、规划成本高等问题,提出一种基于蚁群算法的低碳群体建筑外部边缘空间规划方法。依据城市低碳群体建筑外部边缘空间的模糊特性,引入模糊集合理论对建筑外部边缘空间进行理解和建筑外部边缘空间模糊矩阵的构建,对边缘空间进行划分和限定。结合建筑外部边缘空间的特性和具体关系模式进行空间层次划分,计算空间属性权重,以此确立空间规划目标,根据空间规划目标函数构建空间规划模型,设定求解空间规划模型的蚁群算法信息素更新方式,依据个体信息素转移概率指导个体进行模型最优解搜索。实验结果表明,所提方法与传统的空间规划方法相比,有效减少了计算时间,降低了规划成本。 相似文献