Tank container operators’ profit maximization through dynamic operations planning integrated with the quotation-booking process under multiple uncertainties



Xing, Xinjie ORCID: 0000-0001-6277-5045, Drake, PR ORCID: 0000-0002-5564-0473, Song, Dongping and Zhou, Yang
(2019) Tank container operators’ profit maximization through dynamic operations planning integrated with the quotation-booking process under multiple uncertainties. European Journal of Operational Research, 274 (3). pp. 924-946.

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Abstract

Tank Container Operators (TCOs) are striving to maximize profit through the integration of their global Tank Container (TC) operations with the job quotation-booking process. However, TCOs face a set of unique challenges not faced by general shipping container operators, including the process uncertainties arising from TC cleaning and the use of Freight Forwarders (FFs). In this paper, a simulation-based two-stage optimization model is developed to address these challenges. The first stage focuses on tactical decisions of setting inventory levels and control policy for empty container repositioning. The second stage integrates the dynamic job acceptance/rejection decisions in the quotation-booking processes with container operations decisions in the planning and execution processes, such as job fulfilment, container leasing terms, choice of FFs considering cost and reliability, and empty tank container repositioning. The solution procedure is based on the simulation model combined with heuristic algorithms including an adjusted Genetic Algorithm, mathematical programming, and heuristic rules. Numerical examples based on a real case study are provided to illustrate the effectiveness of the model.Tank Container Operators (TCOs) are striving to maximize profit through the integration of their global Tank Container (TC) operations with the job quotation-booking process. However, TCOs face a set of unique challenges not faced by general shipping container operators, including the process uncertainties arising from TC cleaning and the use of Freight Forwarders (FFs). In this paper, a simulation-based two-stage optimization model is developed to address these challenges. The first stage focuses on tactical decisions of setting inventory levels and control policy for empty container repositioning. The second stage integrates the dynamic job acceptance/rejection decisions in the quotation-booking processes with container operations decisions in the planning and execution processes, such as job fulfillment, container leasing terms, choice of FFs considering cost and reliability, and empty tank container repositioning. The solution procedure is based on the simulation model combined with heuristic algorithms including an adjusted Genetic Algorithm, mathematical programming, and heuristic rules. Numerical examples based on a real case study are provided to illustrate the effectiveness of the model.

Item Type: Article
Uncontrolled Keywords: OR in maritime industry, Profit maximization, Tank container management, Dynamic planning horizon, Uncertainty
Depositing User: Symplectic Admin
Date Deposited: 23 Nov 2018 16:17
Last Modified: 19 Jan 2023 01:11
DOI: 10.1016/j.ejor.2018.10.040
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3029046