Liner ship bunkering and sailing speed planning with uncertain demand
- 1. Tongji University, School of Economics and Management (China)
- 2. Fuzhou university, School of Economics and Management (China)
- 3. Donghua University, Glorious Sun School of Business and Management (China)
Description
Liner shipping is an important branch of maritime transportation. As bunker fuel consumption causes high operating cost and harmful gas emissions, bunker fuel management is a great challenge and a hot research topic in liner shipping. Bunker charging can be achieved at ports with diverse prices, and it is recognized that appropriately managing bunker fuel and sailing speed can improve liner shipping performance and reduce environmental pollution. Most existing works assume that the container demand is deterministic. However, in practice, it is usually difficult to exactly estimate the volume of containers to be shipped due to various factors. This paper studies a liner ship bunkering and speed optimization problem under uncertain container demand. For the problem, a two-stage stochastic and non-linear programming formulation is proposed. To split the complexity of the problem, the complicated bunker consumption function is approximated by piecewise linear ones. To solve the problem, a classic sample average approximation (SAA) method, and the SAA based on scenario reduction, and an L-shaped method are developed and compared. Numerical results show that the L-shaped method outperforms the two SAA methods, in terms of solution quality and computational time.
Additional details
Identifiers
Publishing Information
- Journal Title
- Computational and Applied Mathematics (Online)
- Journal Volume
- 39
- Journal Issue
- 1
- Journal Page Range
- p. 1-23
- ISSN
- 1807-0302
INIS
- Country of Publication
- Brazil
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 51081828
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Descriptors DEI
- APPROXIMATIONS; COMPARATIVE EVALUATIONS; DEMAND; EMISSION; FUEL CONSUMPTION; FUEL MANAGEMENT; FUELS; MATHEMATICAL SOLUTIONS; NONLINEAR PROGRAMMING; OPERATING COST; POLLUTION; PRICES; STOCHASTIC PROCESSES
- Descriptors DEC
- CALCULATION METHODS; COST; ENERGY CONSUMPTION; EVALUATION; MANAGEMENT; NUCLEAR MATERIALS MANAGEMENT
Optional Information
- Copyright
- Copyright (c) 2020 SBMAC - Sociedade Brasileira de Matematica Aplicada e Computacional