PLANNING AND DECISION-MAKING TO INCREASE PRODUCTIVITY ON A MARITIME CONTAINER TERMINAL

被引:0
作者
Twrdy, Elen [1 ]
Beskovnik, Bojan [2 ]
机构
[1] Univ Ljubljana, Fac Maritime Studies & Transport, SI-6320 Portoroz, Slovenia
[2] Intereuropa, Globalni Logisticni Serv, SI-6000 Koper, Slovenia
来源
PROMET-TRAFFIC & TRANSPORTATION | 2008年 / 20卷 / 05期
关键词
Maritime container terminals; productivity; decision model; planning;
D O I
暂无
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
This article describes orientations in optimization of operations on a maritime container terminal. With the application of an adequate model for forecasting, planning and simulating it is possible to increase the productivity and optimize the capacity of the terminal. The emphasis is mainly on setting up the decision making model, in order to raise productivity in all subsystems of the maritime container terminal. Management of a maritime container terminal is a complex process, which includes a vast number of different decisions. The management must develop elements and strategies for checking the productivity and its rise, which can only be achieved through optimization of the entire system. With knowledge about new technologies, operational processes, methods of forecast and simulation it is possible to achieve the easiest usage of different strategies for improving productivity. This is particularly valid for terminals, where the physical extension of the terminal is practically impossible and further development of the system is possible only by searching internal sources. Therefore, the management of a maritime container terminal must develop an appropriate decision support model, in order to make an adequate support to strategic decisions. These decisions relate basically to the assessment of the best development and optimization decisions and on application of proposed solutions in the infrastructure and suprastructure of the terminal.
引用
收藏
页码:335 / 341
页数:7
相关论文
共 50 条
  • [21] Verification and Validation Methods for Decision-Making and Planning of Automated Vehicles: A Review
    Ma, Yining
    Sun, Chen
    Chen, Junyi
    Cao, Dongpu
    Xiong, Lu
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2022, 7 (03): : 480 - 498
  • [22] RESEARCH ON COMPREHENSIVE DECISION-MAKING METHOD FOR CAPACITY PLANNING OF PUMPED STORAGE POWER STATIONS BASED ON MULTI-ATTRIBUTE DECISION-MAKING THEORY
    Zhang, Cheng
    Xia, Pei
    Zhang, Xiaoxing
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2024, 45 (09): : 639 - 646
  • [23] ANALYTICAL MODELS OF EVALUATION OF THE PRODUCTIVITY OF MARITIME CARGO COMPLEXES OF CONTAINER TERMINALS
    Galin, Alexander V.
    Kolosov, Mikhail A.
    Rusinov, Igor A.
    Eglit, Yan Ya.
    MARINE INTELLECTUAL TECHNOLOGIES, 2018, 4 (04): : 249 - 253
  • [24] An In-Depth Security Assessment of Maritime Container Terminal Software Systems
    Eichenhofer, Joseph O.
    Heymann, Elisa
    Miller, Barton P.
    Kang, Arnold
    IEEE ACCESS, 2020, 8 (08): : 128050 - 128067
  • [25] Decision-making framework for an acute care clinical pharmacist productivity model: Part 1
    Vest, Tyler A.
    Simmons, Adrienne
    Morbitzer, Kathryn A.
    McLaughlin, Jacqueline E.
    Cicci, Jonathan
    Clarke, Megan
    Valgus, John M.
    Falato, Chris
    Waldron, Kayla M.
    AMERICAN JOURNAL OF HEALTH-SYSTEM PHARMACY, 2021, 78 (15) : 1402 - 1409
  • [26] Decision-Making and Planning Method for Autonomous Vehicles Based on Motivation and Risk Assessment
    Wang, Yisong
    Wang, Chunyan
    Zhao, Wanzhong
    Xu, Can
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (01) : 107 - 120
  • [27] Integrating a cognitive computational model of planning and decision-making considering affective information
    Cervantes, Jose-Antonio
    Rosales, Jonathan-Hernando
    Lopez, Sonia
    Ramos, Felix
    Ramos, Marco
    COGNITIVE SYSTEMS RESEARCH, 2017, 44 : 10 - 39
  • [28] Multi-objective decision-making model for distribution planning of goods and routing of vehicles in emergency multi-objective decision-making model for distribution planning of goods and routing of vehicles in emergency
    Zahedi, Abdolhamid
    Kargari, Mehrdad
    Kashan, Ali Husseinzadeh
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2020, 48
  • [29] Models for train load planning problems in a container terminal
    Ambrosino, Daniela
    Siri, Silvia
    Advances in Intelligent Systems and Computing, 2014, 262 : 15 - 26