Research on Multitask Collaborative Scheduling Problem with Heuristic Strategies

Fan Zhang; Gui Fa Teng; Jian Bin Ma; Jie Yao

doi:10.4028/www.scientific.net/AMM.66-68.758

Paper Titles

Divided Flow Extrusion of AZ31 Magnesium Alloy with Cerium and Antimony Addition
p.736

Room-Temperature Mechanical Properties and Glass Formation of Zr₅₀Cu₂₀Ni₁₅Al_(15-X)Tix (x=3, 5, 7) Bulk Metallic Glass Alloys
p.741

A Novel Determination Method of IPMC Young’s Modulus Based on Cantilever Resonance Theory
p.747

Free Vibrations of Beams with Arbitrary Boundary Conditions Based on Wave Propagation Method
p.753

Research on Multitask Collaborative Scheduling Problem with Heuristic Strategies
p.758

A Templated Carbon Prepared by Using a Clinoptilolite-Ca Mineral as Template and Furfuralcohol as Carbon Source: Pore Structure and Electrochemical Performance in H₂SO₄
p.764

Effect of Further Calcination on the Phase Structure of LiMn₂O₄ Prepared by a Solution Combustion Synthesis
p.768

The Phase Structure of Fe Doped LiFe_XMn_2-XO₄ Prepared by a Molten-Salt Combustion Synthesis
p.772

Axisymmetric Compression Wave Propagation in a Magneto-Electro-Elastic Cylinder
p.776

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 66-68Research on Multitask Collaborative Scheduling...

Research on Multitask Collaborative Scheduling Problem with Heuristic Strategies

Abstract:

According to problems existed in the current farm machinery scheduling process, a new farm machinery scheduling scheme is adopted in this dissertation. The collaborative scheduling model of farm machinery is established and multitask collaborative scheduling algorithm is designed through analyzing the differences between Vehicle Scheduling Problem and agricultural machinery scheduling in the dissertation. Earliest Start Time First and minimal resource allocated capacity first strategies are used in the farm machinery scheduling. The algorithm is useful for the case of machinery owner with sufficient farm machinery. The experiment proves that the collaborative scheduling algorithm is more effective than the serial scheduling algorithm.

You might also be interested in these eBooks

Mechanical, Materials and Manufacturing Engineering

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 66-68)

Pages:

758-763

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.66-68.758

Citation:

Cite this paper

Online since:

July 2011

Authors:

Fan Zhang, Gui Fa Teng, Jian Bin Ma, Jie Yao

Keywords:

Collaborative Scheduling, Farm Machinery Scheduling, Heuristic Search

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] HuangMinfang. An Intelligent Approach to the Generation of Vehicle Routing Schemes in Distribution. Dalian University of Technology. [D] 2008, p.48-P52.

Google Scholar

[2] ZhongShiquan. Research on Optimization Method for Vehicle Routing in Logistics Distribution. Tianjin University. (2007).

Google Scholar

[3] ShiJun. CaoHan. Research on Heuristic search problem. [J]Microcomputer & its Application. 2004. 10.

Google Scholar

[4] LiuBeilin. GaoShuang. Review of vehicle routing problem algorithm. [J]Business Economics, 2008, 9.

Google Scholar

[5] LanZhou. Research of Scheduling Algorithms in Distributed Systems. [D] University of Electronic Science and Technology of China, (2008).

Google Scholar

[6] GuoHuihuang, LiJun. Vehicle optimal scheduling. [M] Chengdu University of science and technology press, Collaborative (1994).

Google Scholar

[7] YangYanxuan, SongShiji. Review of Heurist algorithm in Vehicle Routing Problem. [D] Tsinghua University.

Google Scholar

[8] MaHuawei. Vehicle Routing Problem with Time Windows and the Study of Heuristics. [D] Hefei University of Technology, (2008).

Google Scholar

[9] Deng Linyi, LinYan, JinChaoguang. Priority rule-based particle swarm optimization for RCPSP. [J] Computer Engineering and Applications, 2009, 45(10).

Google Scholar

[10] ZhangWeizhe, TianZhihong. Multi-Cluster Co-Allocation Scheduling Algorithms in Virtual Computing Environment. [J] Journal of Software, 2007, 18(8).

Google Scholar

[11] TERESA WU, NONG YE and DAWEI Zhang. Comparison of Distributed methods for resource allocation. [J]International Journal of Production Research, 2005, 43(3).

Google Scholar

[12] YaoWeijian. A Study on the Optimization of Resource Constrained Project Portfolio Selection and Scheduling. [D] 2009. Zhejiang University.

Google Scholar

[13] ZouGushan. The Research of Genetic Algorithm for Vehicle Routing Problem. [D] Guangdong University of Technology.

Google Scholar