Fleet co-deployment for liner shipping alliance: Vessel pool operation with uncertain demand

2021 ◽  
Vol 214 ◽  
pp. 105923
Author(s):  
Jihong Chen ◽  
Chenglin Zhuang ◽  
Chen Yang ◽  
Zheng Wan ◽  
Xin Zeng ◽  
...  
Keyword(s):  
Liner Shipping ◽  
Uncertain Demand

Minimax Regret Model for Liner Shipping Fleet Deployment with Uncertain Demand

2016 ◽  
Vol 2549 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Shuaian Wang ◽  
Zhiyuan Liu ◽  
Xiaobo Qu
Keyword(s):  
Liner Shipping ◽  
Uncertain Demand ◽  
Minimax Regret ◽  
Fleet Deployment

Robust container slot allocation with uncertain demand for liner shipping services

2021 ◽  
Author(s):  
Hui Zhao ◽  
Qiang Meng ◽  
Yadong Wang
Keyword(s):  
Liner Shipping ◽  
Uncertain Demand ◽  
Slot Allocation

scholarly journals Integrated Optimization of Port Rotation Direction and Fleet Deployment for Container Liner Shipping Routes

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jingxu Chen ◽  
Yiran Wang ◽  
Xinlian Yu ◽  
Zhiyuan Liu
Keyword(s):  
Demand Uncertainty ◽  
Liner Shipping ◽  
Uncertain Demand ◽  
Multicommodity Flow ◽  
Rotation Direction ◽  
Container Liner Shipping ◽  
Planning Methodology ◽  
Total Network ◽  
Selection Of ◽  
Fleet Deployment

This paper provides an integrated planning methodology for the optimization of port rotation direction and fleet deployment for container liner shipping routes with consideration of demand uncertainty. We first consider a special case that demand is deterministic. A multicommodity flow network model is developed via minimizing the total network-wide cost. Its decisions are the selection of port rotation direction and fleet deployment and container routings in the shipping network. Afterward, we address the generic case that uncertain demand is considered, which is represented by potentially realizable demand scenarios. We develop a minimax regret model to procure the least maximum regret across all the demand scenarios. The proposed models are applied to an Asia-Europe-Oceania liner shipping network with 46 ports and 12 ship routes. Results could provide the liner company with a comprehensive decision tool to simultaneously determine port rotation direction and fleet deployment when tackling uncertain demand.

The Simultaneous Determination of Plant and Leased Warehouse Capacities for a Firm Facing Uncertain Demand in Several Regions

1982 ◽  
Vol 14 (2) ◽  
pp. 99-108 ◽  
Author(s):  
James V. Jucker ◽  
Robert C. Carlson ◽  
Dean H. Kropp
Keyword(s):  
Simultaneous Determination ◽  
Uncertain Demand

Robust Control of Distribution Networks with Uncertain Demand

1992 ◽  
Author(s):  
Franco Blanchini ◽  
Franca Rinaldi ◽  
Walter Ukovich
Keyword(s):  
Robust Control ◽  
Distribution Networks ◽  
Uncertain Demand

A Liner Shipping Network Design

2013 ◽  
Author(s):  
Volker Windeck
Keyword(s):  
Network Design ◽  
Liner Shipping

Schedule Reliability in Liner Shipping Timetable Design: A Convex Programming Approach

2020 ◽  
Author(s):  
Abraham Zhang ◽  
Zhichao Zheng ◽  
Chung-Piaw Teo
Keyword(s):  
Convex Programming ◽  
Liner Shipping ◽  
Programming Approach ◽  
Schedule Reliability

Dynamic Monopoly Pricing Under a Poisson-Type Uncertain Demand

1992 ◽  
Vol 65 (4) ◽  
pp. 593 ◽  
Author(s):  
Yu-Min Chen ◽  
Dipak C. Jain
Keyword(s):  
Uncertain Demand ◽  
Monopoly Pricing ◽  
Dynamic Monopoly ◽  
Poisson Type

Decision-making for location of manufacturing bases in an uncertain demand situation

2021 ◽  
pp. 1-13
Author(s):  
Sun Jianzhu ◽  
Zhang Qingshan ◽  
Yu Yinyun
Keyword(s):  
Site Selection ◽  
Fuzzy Numbers ◽  
Uncertain Demand ◽  
Quick Response ◽  
Time Cost ◽  
Location Selection ◽  
Manufacturing Enterprises ◽  
Service Efficiency ◽  
Equipment Manufacturing ◽  
Smart Industry

Multi-site selection is a hot research issue for equipment manufacturing enterprises. With the development of smart industry, equipment manufacturing enterprises have entered the era of personalized and small batch manufacturing. Enterprises want to better meet customer needs and win competition, they must carry out scientific factory planning and site selection, so as to ensure quick response to the market. Based on this, this paper proposes a two-stage location selection model. Firstly, the method uses fuzzy numbers to express the demand size of demand points. Secondly, the distance factor is used as a criterion to select the candidate manufacturing bases with sufficient available resources. Next, the location model of enterprise manufacturing base is established which the goal of maximizing service efficiency and the constraints of time, cost and demand. Finally, a random numerical example is used to simulate the model, and lingo is used to solve it.

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