Logistics Performance Index-driven in operational planning for logistics companies: A smart transportation approach

被引:1
作者
Dini, Niloofar [1 ]
Yaghoubi, Saeed [2 ]
Bahrami, Hamideh [2 ]
机构
[1] Univ Otago, Sch Geog, Dunedin 9016, New Zealand
[2] Iran Univ Sci & Technol, Sch Ind Engn, Narmak 1684613114, Tehran, Iran
关键词
Route selection; Logistics performance index; Multimodal transport; Time uncertainty; Smart containers; CUSTOMER SATISFACTION; ROUTE SELECTION; TIME WINDOWS; SERVICE QUALITY; DELIVERY TIME; CONSOLIDATION; OPTIMIZATION; IMPACT; MANAGEMENT; MODELS;
D O I
10.1016/j.tranpol.2024.10.034
中图分类号
F [经济];
学科分类号
02 ;
摘要
The responsibility of Logistics Companies (LCs) extends beyond simply handling logistical processes and choosing transportation routes; they focus on being competitive and efficient in their operations. In multiple origins and destinations networks, LCs attempt to select the most optimal routes from each point. To address this challenge and reduce the time needed to identify potential routes, a novel method has been developed in this research for LCs. In operational planning, additional factors need to be considered to increase efficiency, customer satisfaction, and competitiveness. To confront this issue, the study proposes a novel model and contributions, inspired by the LPI, to apply the transformative impact of smart ports, the integration of smart containers, the choices of clearing and forwarding agents and port operators, and time uncertainty in the multiobjective framework. Specifically, the mathematical model's objectives include cost, time, customer satisfaction, and environmental impact in the periodic multimodal network. An innovative customer satisfaction function is introduced by integrating the selection of smart containers and smart ports, emphasizing their impact on enhancing customer satisfaction, while addressing time uncertainty through a chance-constrained approach and coefficients of variation. The model is solved using goal programming, and the results show that smart ports and smart containers can majorly affect transportation time and customer satisfaction. Furthermore, comparing the results to other studies demonstrates its superiority in decision-making for LCs, particularly by including time uncertainty and the role of clearing and forwarding agents and port operators. Therefore, the model holds practical significance in lowering costs, enhancing customer satisfaction, and facilitating smart international logistics. This research offers insights that are not only useful for the LCs but also for other stakeholders in the transport industry.
引用
收藏
页码:42 / 62
页数:21
相关论文
共 72 条
  • [1] Multi-product multi-period Inventory Routing Problem with a transshipment option: A green approach
    Al-e-Hashem, S. M. J. Mirzapour
    Rekik, Yacine
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2014, 157 : 80 - 88
  • [2] Arnold J., 2011, African Trade Policy Notes
  • [3] Assessing the economic and environmental impact of freight transport sectors in Thailand using computable general equilibrium model
    Boonpanya, Tanawat
    Masui, Toshihiko
    [J]. JOURNAL OF CLEANER PRODUCTION, 2021, 280
  • [4] Cetinkaya C., 2021, LOGISTICS SUPPLY CHA
  • [5] A Multi-Objective Goal Programming airport selection model for low-cost carriers' networks
    Chang, Yu-Chun
    Lee, Ning
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2010, 46 (05) : 709 - 718
  • [6] MANAGEMENT MODELS AND INDUSTRIAL APPLICATIONS OF LINEAR-PROGRAMMING
    CHARNES, A
    COOPER, WW
    [J]. MANAGEMENT SCIENCE, 1957, 4 (01) : 38 - 91
  • [7] OPTIMAL ESTIMATION OF EXECUTIVE COMPENSATION BY LINEAR PROGRAMMING
    Charnes, A.
    Cooper, W. W.
    Ferguson, R. O.
    [J]. MANAGEMENT SCIENCE, 1955, 1 (02) : 138 - 151
  • [8] Route optimization in township logistics distribution considering customer satisfaction based on adaptive genetic algorithm
    Cui, Huixia
    Qiu, Jianlong
    Cao, Jinde
    Guo, Ming
    Chen, Xiangyong
    Gorbachev, Sergey
    [J]. MATHEMATICS AND COMPUTERS IN SIMULATION, 2023, 204 : 28 - 42
  • [9] A fast and elitist multiobjective genetic algorithm: NSGA-II
    Deb, K
    Pratap, A
    Agarwal, S
    Meyarivan, T
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) : 182 - 197
  • [10] Dee P., 2008, Infrastruc. trade Asia, P28