﻿ 双资源多目标集成协作计划与调度模型及其求解算法 A Multi-Objective Integrated Model and Its Algorithm of Collaborative Planning and Scheduling for Dual-Resource

Management Science and Engineering
Vol.06 No.02(2017), Article ID:21045,12 pages
10.12677/MSE.2017.62009

A Multi-Objective Integrated Model and Its Algorithm of Collaborative Planning and Scheduling for Dual-Resource

Qianqian Hu, Chencheng Ma, Yue Sun, Zhenqiang Bao, Yun Kan

School of Information Engineering, Yangzhou University, Yangzhou Jiangsu

Received: May 31st, 2017; accepted: Jun. 18th, 2017; published: Jun. 21st, 2017

ABSTRACT

Since the problem of that collaborative plan, manufacturing plan and the scheduling solutions are hard to be paralleled and synchronized, the multi-objective model of integrated collaborative plan and scheduling for dual-resource is established, taking the collaborative planning into consideration under the environment of supply chain. There are three objectives in the model: the shortest completion time, the lowest cost and the minimum total tardiness. Take machines and workers as two kinds of constrained resources. Then, the improved SPEA2 algorithm is designed. In this algorithm, the chromosome pair encoding which is suitable for dual-resource and collaborative decision is designed. It includes the process coding, the machine coding, the worker coding and the collaborative decision variable. Finally, the correctness of the model and the efficiency of the algorithm are proved by the simulation experiment.

Keywords:Collaborative Planning, Multi-Objective, Integrated Model, Dual-Resource Scheduling

1. 引言

2. 建立模型

2.1. 问题描述

2.2. 目标函数

，其中

3. 算法设计

3.1. 编码方式

Figure 1. Chromosome encoding with collaboration

3.2. 选择操作

，然后进行繁殖选择(Mating Selection)。整体的平均时间复杂度为，具体选择过程

3.3. 交叉操作

Figure 2. Cutting diagram about archive set of SPEA2

Figure 3. Crossover operation of procedure

Figure 4. Crossover operation of machine

Figure 5. Crossover operation of collaborative decision variable chromosome

3.4. 变异操作

4. 仿真与分析

Figure 6. Mutation operation of procedure

Figure 7. Mutation operation of machine

Figure 8. Mutation operation of collaborative decision variable chromosome

Table 1. Cost of raw materials

Table 2. Detailed processing parameters in production scheduling

Table 3. Worker set corresponding to each machine and impact factor

Table 4. Processing fees per unit time

Table 5. Pareto optimal solution set of the dual-resource scheduling with collaboration

Figure 9. Gantt with collaboration

Figure 10. Gantt without collaboration

5. 结束语

A Multi-Objective Integrated Model and Its Algorithm of Collaborative Planning and Scheduling for Dual-Resource[J]. 管理科学与工程, 2017, 06(02): 71-82. http://dx.doi.org/10.12677/MSE.2017.62009

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