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
Ship air emissions are recognized as one of the key concerns of the maritime industry.Competent authorities have issued various regulations to manage air emissions from ships.Although the authorities are policy makers...Ship air emissions are recognized as one of the key concerns of the maritime industry.Competent authorities have issued various regulations to manage air emissions from ships.Although the authorities are policy makers,the effectiveness of policies is up to the shipping industry who operates the vessels and terminals to fulfill maritime transportation works.Given this characteristic,bi-level optimization model has been widely adopted in studies that optimize policy design or evaluate its effectiveness.The framework of a typical bi-level optimization model for ship emission management problem is given to show the basic structure of similar issues.A series of applications of bi-level optimization model in managing ship emissions is reviewed,including cases of Energy Efficiency Design Index,Emissions Control Area,Market Based Measure,Carbon Intensity Indicator,and Vessel Speed Reduction Incentive Program.We hope this paper can enlighten scholars interested in this area and provide help for them.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.
基金supported by the National Natural Science Foundation of China(72071173,71831008).
文摘Ship air emissions are recognized as one of the key concerns of the maritime industry.Competent authorities have issued various regulations to manage air emissions from ships.Although the authorities are policy makers,the effectiveness of policies is up to the shipping industry who operates the vessels and terminals to fulfill maritime transportation works.Given this characteristic,bi-level optimization model has been widely adopted in studies that optimize policy design or evaluate its effectiveness.The framework of a typical bi-level optimization model for ship emission management problem is given to show the basic structure of similar issues.A series of applications of bi-level optimization model in managing ship emissions is reviewed,including cases of Energy Efficiency Design Index,Emissions Control Area,Market Based Measure,Carbon Intensity Indicator,and Vessel Speed Reduction Incentive Program.We hope this paper can enlighten scholars interested in this area and provide help for them.
