Integrated cross-supplier order and logistic scheduling in cloud manufacturing

被引:22
作者
Wu, Qiao [1 ]
Xie, Naiming [1 ]
Zheng, Shaoxiang [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Econ & Management, Nanjing, Peoples R China
基金
中国国家自然科学基金;
关键词
Cloud manufacturing; integrated scheduling; logistic scheduling; order allocation; improved shuffled frog-leaping algorithm;
D O I
10.1080/00207543.2020.1867921
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the cloud manufacturing environment, integrated cross-supplier order and logistic scheduling can benefit both suppliers and third-party logistics, significantly reduce their production and transport costs to improve the overall efficiency of the supply chain. This paper aims to construct a hybrid solution with both cross-supplier order assignments and third-party logistics scheduling under a centralised scheduling mode of cloud manufacturing platform, which is defined as an integrated cross-supplier order and logistic scheduling (ICSOLS) problem. Since the problem is NP-hard, a strategy based on an improved shuffled frog-leaping algorithm was developed for solving the model. A numerical case was designed for demonstrating the modelling process and analysing results. Different scales of simulations are designed to verify validity and robustness. Results show the proposed approach and algorithm can solve the defined problem efficiently.
引用
收藏
页码:1633 / 1649
页数:17
相关论文
共 38 条
[21]   A novel hybrid multi-objective shuffled frog-leaping algorithm for a bi-criteria permutation flow shop scheduling problem [J].
Rahimi-Vahed, Alireza ;
Dangchi, Mostafa ;
Rafiei, Hamed ;
Salimi, Ehsan .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2009, 41 (11-12) :1227-1239
[22]   Co-creation and user innovation: The role of online 3D printing platforms [J].
Rayna, Thierry ;
Striukova, Ludmila ;
Darlington, John .
JOURNAL OF ENGINEERING AND TECHNOLOGY MANAGEMENT, 2015, 37 :90-102
[23]   A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition [J].
Seghir, Fateh ;
Khababa, Abdellah .
JOURNAL OF INTELLIGENT MANUFACTURING, 2018, 29 (08) :1773-1792
[24]   Multi-objective imperfect preventive maintenance optimisation with NSGA-II [J].
Su, Chun ;
Liu, Yang .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2020, 58 (13) :4033-4049
[25]   FC-PACO-RM: A Parallel Method for Service Composition Optimal-Selection in Cloud Manufacturing System [J].
Tao, Fei ;
LaiLi, Yuanjun ;
Xu, Lida ;
Zhang, Lin .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2013, 9 (04) :2023-2033
[26]   Incorporating order acceptance, pricing and equity considerations in the scheduling of cloud manufacturing systems: matheuristic methods [J].
Vahedi-Nouri, Behdin ;
Tavakkoli-Moghaddam, Reza ;
Hanzalek, Zdenek ;
Arbabi, Hamidreza ;
Rohaninejad, Mohammad .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2021, 59 (07) :2009-2027
[27]   A many-objective memetic algorithm for correlation-aware service composition in cloud manufacturing [J].
Wang, Fei ;
Laili, Yuanjun ;
Zhang, Lin .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2021, 59 (17) :5179-5197
[28]  
WANG YL, 2019, INT J PROD RES, V57
[29]   Logistics 4.0: a systematic review towards a new logistics system [J].
Winkelhaus, Sven ;
Grosse, Eric H. .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2020, 58 (01) :18-43
[30]  
XU X, 2012, ROBOT CIM-INT MANUF, V28