With ongoing global industrialization,the demand for refined oil products,particularly in developing countries,is increasing significantly.Shipping companies typically transport refined oil from a primary refinery to ...With ongoing global industrialization,the demand for refined oil products,particularly in developing countries,is increasing significantly.Shipping companies typically transport refined oil from a primary refinery to multiple oil depots,addressing various demand tasks.To manage uncertain refined oil demand,shipping companies use both self-owned tankers and outsourced tankers,including time-chartered and voyage-chartered tankers.A time charter is a contract where the shipping company pays charter money for a specific period,while a voyage charter involves payments based on voyage frequency.This paper develops a nonlinear programming model to optimize fleet deployment,considering transportation costs and penalty costs for capacity loss during a planning period.Additionally,the model is extended to allow flexible charter types,meaning that time-chartered and voyage-chartered tankers are interchangeable based on shipping demands.A heuristic algorithm based on tabu search is designed to solve the proposed models,and four search operators are incorporated to enhance algorithm efficiency.The models and algorithms are validated using a real tanker fleet.Numerical experiments demonstrate the efficiency of the improved tabu search algorithm in obtaining exact solutions for small-scale instances.The case study indicates that the shipping company prefers waiting for tasks to avoid ship delay penalties and provide high-quality services.Moreover,the flexible charter strategy can reduce shipping costs by 16.34%.These findings offer management insights for determining charter contracts for ship fleets.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.71871037).
文摘With ongoing global industrialization,the demand for refined oil products,particularly in developing countries,is increasing significantly.Shipping companies typically transport refined oil from a primary refinery to multiple oil depots,addressing various demand tasks.To manage uncertain refined oil demand,shipping companies use both self-owned tankers and outsourced tankers,including time-chartered and voyage-chartered tankers.A time charter is a contract where the shipping company pays charter money for a specific period,while a voyage charter involves payments based on voyage frequency.This paper develops a nonlinear programming model to optimize fleet deployment,considering transportation costs and penalty costs for capacity loss during a planning period.Additionally,the model is extended to allow flexible charter types,meaning that time-chartered and voyage-chartered tankers are interchangeable based on shipping demands.A heuristic algorithm based on tabu search is designed to solve the proposed models,and four search operators are incorporated to enhance algorithm efficiency.The models and algorithms are validated using a real tanker fleet.Numerical experiments demonstrate the efficiency of the improved tabu search algorithm in obtaining exact solutions for small-scale instances.The case study indicates that the shipping company prefers waiting for tasks to avoid ship delay penalties and provide high-quality services.Moreover,the flexible charter strategy can reduce shipping costs by 16.34%.These findings offer management insights for determining charter contracts for ship fleets.
