Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming

被引:17
|
作者
Alessandri, Angelo [1 ]
Cervellera, Cristiano [2 ]
Cuneo, Marta [2 ]
Gaggero, Mauro [1 ,2 ]
Soncin, Giuseppe [2 ]
机构
[1] Univ Genoa, Dept Prod Engn Thermoenerget & Math Models DIPTEM, I-16129 Genoa, Italy
[2] Natl Res Council Italy, Inst Intelligent Syst Automat ISSIA CNR, I-16149 Genoa, Italy
关键词
container terminal; dynamic model; mixed-integer programming; nonlinear programming; predictive control;
D O I
10.1057/mel.2008.24
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The increase in efficiency of container terminals is addressed via an approach based on the optimisation of logistics operations. Toward this end, a discrete-time dynamic model of the various flows of containers that are inter-modally routed from arriving carriers to carriers ready for departure is proposed. On the basis of such a model, the decisions on the allocation of the available handling resources inside a container terminal are made according to the predictive-control approach by minimising a performance cost function over a forward horizon from the current time instant. Since both the dynamic equations and the cost function are in general nonlinear and since binary variables are used to model the departure or stay of a carrier, such decisions result from the on-line solution of a mixed-integer nonlinear programming problem at each time step. To solve this problem, two techniques are proposed that have to deal explicitly with the binary variables and with the nonlinearities of the model and the cost function. The first relies on the application of a standard branch-and-bound algorithm. The second is based on the idea of treating the decisions associated with the binary variables as step functions. Simulation results are reported to illustrate the pros and cons of such methodologies in a case study.
引用
收藏
页码:58 / 76
页数:19
相关论文
共 50 条
  • [21] Modelling of Stability of Economic Systems Using Benchmarking and Dynamic Programming
    Jurenoks, Vitalijs
    Jansons, Vladimirs
    Didenko, Konstantins
    2008 UKSIM TENTH INTERNATIONAL CONFERENCE ON COMPUTER MODELING AND SIMULATION, 2008, : 295 - 300
  • [22] Research on logistics management layout optimization and real-time application based on nonlinear programming
    Zhang, Yanqi
    Kou, Xiaofei
    Song, Zhigang
    Fan, Yuqing
    Usman, Mohammed
    Jagota, Vishal
    NONLINEAR ENGINEERING - MODELING AND APPLICATION, 2021, 10 (01): : 526 - 534
  • [24] Midterm Hydrothermal Generation Scheduling Using Nonlinear Dynamic Programming
    Nechaev, I.
    Palamarchuk, S.
    2013 IEEE GRENOBLE POWERTECH (POWERTECH), 2013,
  • [25] Lake eutrophication management modeling using dynamic programming
    Kuo, Jan-Tai
    Hsieh, Pin-Hui
    Jou, Wei-Shin
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2008, 88 (04) : 677 - 687
  • [26] Solving ecological management problems using dynamic programming
    Grüne, L
    Kato, M
    Semmler, W
    JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION, 2005, 57 (04) : 448 - 473
  • [27] The Concept on Nonlinear Modelling of Dynamic Objects Based on State Transition Algorithm and Genetic Programming
    Bartczuk, Lukasz
    Dziwinski, Piotr
    Red'ko, Vladimir G.
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2017, PT II, 2017, 10246 : 209 - 220
  • [28] THE COMPLEXITY OF SUPPLY CHAIN SYSTEM'S LOGISTICS FINANCIAL MANAGEMENT AND DYNAMIC NONLINEAR SYSTEM
    Miao, Yu
    Jin, Xin
    Alsulami, Abdulaziz A.
    Kong, Menglei
    Xu, Pang
    FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY, 2022, 30 (02)
  • [29] Optimization of sequential subdivision of depth of cut in turning operations using dynamic programming
    Lu, Kaibo
    Jing, Minqing
    Zhang, Xiaoli
    Liu, Heng
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2013, 68 (5-8): : 1733 - 1744
  • [30] Optimization of sequential subdivision of depth of cut in turning operations using dynamic programming
    Kaibo Lu
    Minqing Jing
    Xiaoli Zhang
    Heng Liu
    The International Journal of Advanced Manufacturing Technology, 2013, 68 : 1733 - 1744