Description: 遗传算法在大学排课问题中的应用，对制作排课系统有重要的参考价值-Genetic Algorithm in the University Timetable Problem of Course Scheduling System has produced an important reference value Platform: |
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Author:xiaohui |
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Description: 排课问题是一个有约束的、多目标的组合优化问题，并且已经被证明是一个NP完全问题。
遗传算法借鉴生物界自然选择和自然遗传机制，使用群体搜索技术，尤其是用于处理传统搜索方法难以解决的复杂的和非线性的问题。经过近40年的发展，遗传算法在理论研究和实际应用中取得了巨大的成功，本文将遗传算法用于排课问题的求解，首先讨论了排课问题中的影响因素、主要约束条件、求解目标和难点，并用数学模型完整地描述了排课问题。其次对多个模糊排课目标进行了定量分析，建立了排课优化目标空间。针对排课问题研究了染色体编码方式以及遗传算子的设计，提出了适应度函数的计算方法。最后对排课问题进行了实验。实验结果表明，其过程的目标值跟踪显示，算法稳健趋优，所得结果令人满意。-Course Scheduling problem is a constrained, multi-objective optimization problem, and has proven to be a NP complete problem.
Genetic algorithms reference biosphere and the natural genetic mechanism of natural selection, using the group search technology, particularly the traditional search methods for handling complex and difficult to solve nonlinear problems. After nearly 40 years of development, the genetic algorithm in the theoretical study and practical application was a great success, this paper genetic algorithm for solving the course timetabling problem, first discussed the impact of factors in the course arrangement, the main constraints, to solve goals and difficulties, and a complete mathematical model to describe the course arrangement. Arranging multiple fuzzy goals followed by a quantitative analysis, the optimal target Arranging space. Arranging for the Study of the chromosome coding and genetic operators design, proposed fitness function is calculated. Finally, the co Platform: |
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Author:张林杰 |
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Description: 用 MATLAB实现作业车间调度的遗传算法源程序，基本思路可供参考。希望对大家有所帮助。- Realization of job-shop scheduling based on genetic algorithm by using MATLAB soft. wish help to others. Platform: |
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Author:wllx |
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Description: 遗传算法车间调度,车间作业调度问题遗传算法
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输入参数列表
M 遗传进化迭代次数
N 种群规模(取偶数)
Pm 变异概率
T m×n的矩阵，存储m个工件n个工序的加工时间
P 1×n的向量，n个工序中，每一个工序所具有的机床数目
输出参数列表
Zp 最优的Makespan值
Y1p 最优方案中，各工件各工序的开始时刻，可根据它绘出甘特图
Y2p 最优方案中，各工件各工序的结束时刻，可根据它绘出甘特图
Y3p 最优方案中，各工件各工序使用的机器编号
Xp 最优决策变量的值，决策变量是一个实数编码的m×n矩阵
LC1 收敛曲线1，各代最优个体适应值的记录
LC2 收敛曲线2，各代群体平均适应值的记录
最后，程序还将绘出三副图片：两条收敛曲线图和甘特图（各工件的调度时序图）-Genetic algorithm scheduling, job shop scheduling problems with genetic algorithms -------------------------------------------------------------------------- genetic evolution of the input parameter list, the number of iterations M N population size (taken even) Pm mutation probability T m × n matrix, stored m one piece n a process of processing time 1 × n vector, n a process in which each machine processes the number of Zp with the best value Y1p Optimal Makespan programs, the start time of each process the workpiece can be drawn based on its optimal solution Gantt Y2p, each time the workpiece end of the process, according to its draw Gantt Y3p optimal solution, each piece of the processes using machine code Xp optimal decision variable, decision variable is a real m × n matrix encoded LC1 convergence curve 1, the generation of the best individual record of LC2 fitness convergence curve 2, the average fitness value on behalf of groups record Finally, the program will draw three pict Platform: |
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Author:王龙隐 |
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Description: 本文通过遗传算法解决基本的无时限车辆调度问题。采用车辆和客户对应排列编码的遗传算法，通过种群初始化，选择，交叉，变异等操作最终得到车辆配送的最短路径。通过MATLAB仿真结果可知，通过遗传算法配送的路径为61.5000km,比随机配送路径67km缩短了5.5km。此结果表明遗传算法可以有效的求解VRP问题。(In this paper, genetic algorithm is used to solve the basic vehicle scheduling problem without time limit. Using the genetic algorithm of vehicle and customer corresponding permutation coding, through the initialization of population, selection, crossover and mutation, the shortest route of vehicle delivery is obtained. Through MATLAB simulation results, we can see that the route of delivery through genetic algorithm is 61.5000km, which is 5.5km shorter than the random delivery path 67km. The results show that the genetic algorithm can solve the VRP problem effectively.) Platform: |
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Author:阿雨
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Search - scheduling using genetic in matlab