Dynamic and stochastic models for the allocation of empty containers
Operations Research
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Dynamic Control of Logistics Queueing Networks for Large-Scale Fleet Management
Transportation Science
A simulated annealing approach for the multi-periodic rail-car fleet sizing problem
Computers and Operations Research
Hi-index | 0.00 |
Container fleet sizing is a key issue in liner shipping industry. Although container shipping is an intermodal transport system, inland container movements are often beyond the control of shipping lines. It is vital to understand how the inland transport times and their variability affect the container fleet sizing. This paper first formulates the container fleet sizing problem in liner services with uncertain customer demands and stochastic inland transport times. Simulation-based optimisation approaches are then employed to solve the problem. Two typical shipping services, one cyclic route in trans-Pacific lane and the other more complicated route in Europe---Asia lane, are used as case studies. A quantitative relationship between the optimal container fleet size and the inland transport time is established. The impact of uncertainties in inland times on the fleet sizing is also investigated. The results provide shipping companies useful insights into making strategic decisions.