2019, 11(5): 108-112. doi: 10.16670/j.cnki.cn11-5823/tu.2019.05.17
装配式PC构件车辆调度问题研究
西安建筑科技大学 土木工程学院，西安 710055 |
Research on Vehicle Scheduling Problem of PC Component
College of Civil Engineering, Xi′an University of Construction and Technology, Xi′an 710055, China |
引用本文:
段海宁, 王茹. 装配式PC构件车辆调度问题研究[J]. 土木建筑工程信息技术,
2019, 11(5): 108-112.
doi: 10.16670/j.cnki.cn11-5823/tu.2019.05.17
Citation:
Duan Haining, Wang Ru. Research on Vehicle Scheduling Problem of PC Component[J]. Journal of Information Technologyin Civil Engineering and Architecture,
2019, 11(5): 108-112.
doi: 10.16670/j.cnki.cn11-5823/tu.2019.05.17
摘要:装配式PC构件体量大，配送频次高，使装配式PC构件运输成本成为影响PC构件成本构成的主要因素之一。研究传统车辆调度问题、粒子群算法、运输影响因素，建立了基于车辆油耗和车辆租赁、人工成本的PC构件运输成本模型。使用精确算法能够计算其最优解但耗时耗力，传统的粒子群算法存在一定缺陷，因此采用改进粒子群算法与精确算法对一个实例进行求解，得到了两种方式下车辆调度方案和综合最优成本相同，证明了改进粒子群算法的正确性和有效性，为求解此类问题提供了良好的方法。
Abstract: Considering the large amount of prefabricated PC component and the high frequency of distribution, the transportation cost of the prefabricated PC component becomes one of the main factors affecting the cost composition of PC components. This paper researches on the traditional vehicle scheduling problem, particle swarm optimization algorithm and transportation influence factors, and establishes the transportation cost model of PC component based on vehicle fuel consumption and vehicle rental and artificial cost. Using precise algorithm is able to calculate the optimal solution but time-consuming, and traditional particle swarm optimization algorithm has some defects. So, with the improved particle swarm optimization algorithm and accurate algorithm for an instance, vehicle scheduling scheme is obtained under two ways and comprehensive optimal cost is the same, which proves the correctness and effectiveness of the improved particle swarm algorithm that provides a good method to solve such problem.
| [1] |
于龙飞, 张家春.基于BIM的装配式建筑集成建造系统[J].土木工程与管理学报, 2015, 32(4): 73-79.doi: 10.3969/j.issn.2095-0985.2015.04.012 |
| [2] |
李颖.基于价值链模型的装配整体式建筑成本分析研究[J].中国管理信息化, 2016, 19(7): 10-14.doi: 10.3969/j.issn.1673-0194.2016.07.004 |
| [3] |
武长青.谈装配式建筑与传统建筑造价对比分析[J].山西建筑, 2017, 43(10): 224-225.doi: 10.3969/j.issn.1009-6825.2017.10.120 |
| [4] |
王雪艳, 何晓珊, 王莉, 等.预制装配式住宅建造成本及控制措施研究[J].建筑经济, 2017, 38(2): 31-34. |
| [5] |
李萍萍.装配式预制构件配送成本优化研究[D].西安建筑科技大学, 2016. |
| [6] |
潘寒, 黄熙萍, 靳华中, 等.基于遗传算法的PC构件工厂排产研究[J].土木建筑工程信息技术, 2018, 10(6): 113-118. |
| [7] |
Fisher M L, Jaikumar R.A generalized assignmentheuristic for vehicle routing[J]. Networks, 1981, 33(11): 109-124. |
| [8] |
蔡宁, 张欢欢, 蒋宇一.用于道路施工进度计划分包与调度优化的改进异构环境最早结束时间算法[J].土木建筑工程信息技术, 2014, 6(5): 6-15.doi: 10.3969/j.issn.1674-7461.2014.05.002 |
| [9] | |
| [10] | |
| [11] |
Kennedy J, Eberhart R.Particle Swarm Optimization[C]. In: Proceeding of IEEE International Conference on Neural Networks, Piscataway, NJ: IEEE CS, 1995: 1942-1948. |
| [12] |
黄洋, 鲁海燕, 许凯波, 等.基于S型函数的自适应粒子群优化算法[J].计算机科学, 2019, 46(1): 245-250. |
| [13] |
Shi Y, Eberhart R C.A modified paticle swarm optimizer[A]. Proceedings of IEEE International Congress Conference on Evolutionary Computation[C]. Piscataway, NJ, Anchorage, AK USA: IEEE service center, 1998, 69-73. |
| [14] |
胡小宇, 刘庆, 贺文宁, 等.基于粒子群算法的单仓储多车物流配送优化[J].计算机应用, 2018, 38(S2): 21-26. |
| [15] |
吴斌.物流配送车辆路径问题及其智能优化算法[M].经济管理出版社, 2013, 64-66+92-95. |
计量
- PDF下载量(31)
- 文章访问量(2305)
- HTML全文浏览量(1152)
