Abstract

1. Abstract The work describes a mathematical programming model for a cargo selection problem, obtained from a Singapore shipping company (APL). Our model helps in evaluating whether a forecast demand should be selected or not. Given the forecasting and a finite set of candidate routes, the model calculates the number of containers transported between port pairs, according to specific customer, equipment type and size and service requirement. This model also concerns the empty container reposition.

2. Background Introduction

3. Background Introduction Demand Forecasting • A joint work of demand planner, sales manager and trade manager. • Demand forecasting is carried out at three different levels: • Long term forecasting • Median & short term forecasting For the strategic decisions, such as the design of fleets, the design of sea transport systems and long term revenue management • Long term forecasting • Median term forecasting • Short term forecasting Mainly focus on the tactical and operational planning respectively. The selection of origin-destination pairs, selection of costumers, fleet deployment and so on are dependent on the data.

4. Background Introduction A High Degree of Uncertainty • It is possible that not all the forecast demands can be shipped in a period because of the bad weather. • From time to time, there are also many extra profit opportunities offered by the variable markets. Two Examples: It is critical for shipping company to manage revenue based on the cargo selection.

5. Background Introduction Empty Container Reposition • A major component of a shipping company's total operating cost • Due to the imbalance of the international trading In light of the above, it is necessary to have an efficient policy to manage the movement of forecast demand (including laden containers and empty containers) in order to maximize the total profit in a specific planning horizon, and at the same time, to make best use of the existing facilities.

6. Problem Description

7. Problem Description Forecast Demand Record • loading port, i.e., origin • discharging port, i.e., destination • customer • equipment type and size, ETS • service requirement Each forecast demand record is characterized by:

8. Problem Description Equipment Type and Size • Equipment type and size or ETS is the value denoting the type and size of containers which is used for moving cargoes. For example, `D40H' means dry container with the size of 40 feet high cube. The different equipment type and size are shown in the following table: Note: This table is copied from APL website

9. Problem Description Service Requirement • The liner shipping company provides regular service among major ports on a determined schedule basis. • A service depends upon a number of factors, such as seasonal fluctuations, market requirements, company policy etc. • Customer may have specific service requirement.

10. Problem Description Route Definition • In practice, most of shipping companies use concept route, which differs from the service, for operation convenience. • There is a fact that only services are visible for customers or shippers. • Service leg.

11. (i,j,k,m,n) represents the value for forecast demand dimension, i.e., origin-destination pairs, customer, ETS and service requirement. We label this forecast demand dimension (i,j,k,m,n) as f and simply call df a laden cargo demand flow from port i to port j. Empty container reposition demand e can be characterized by origin-destination pairs and ETS, notated as e:(i,j,m). Another flow from port i to port j. Problem Description Forecast Demand Conclusion We assume that shipping company has all the required demand forecasts for any markets they plan to serve. Laden Cargo Demand Empty Container Reposition Demand We want to assign each cargo demand forecast f and e to some mix of routes r among a finite set of candidate routes considered by the shipping company, to optimize our objective.

12. Problem Description Valid Route Not all the routes in candidate set will be appropriated to each demand: • Cargo between i and j can only be transported if the ship sails from i to j, directly or indirectly. • Service requirement should be satisfied. Definition:

13. Problem Description Problem Description • The decision making problem is to assign cargo demands to each route in the `best possible' way. • The objective is to maximize the revenue of optional cargoes minus the variable cost, under a set of different constraints such as demand constraint, network balance constraint, vessel capacity constraint etc. • There are two decisions should be made: • To decide which cargo demand should be moved; • To decide to move the cargo demand on which route.

14. Problem Description Assumptions • All the ships available during the planning horizon are known and fixed. • The forecast demand of cargo, i.e., number of containers from port i to port j over the planning horizon is deterministic, known and occurs uniformly during the horizon. • There are sufficient empty container relocation demand, i.e., de is a big number. It seems more practical to give this assumption since the shipping company only makes the empty container reposition planning. • The managers of the shipping company can suggest a finite set of candidate routes for their liner fleet, derived from common sense, their past experience or their view of future main cargo flows.

15. Problem Description Related Problem • Ship routing and scheduling problem: to find optimal route for each ship and the cargo it carries for any port pair whereas the frequency of service are also calculated. • In our model, the concept of route is expanded and one route can be fulfilled by one or more ships to satisfy the cargo demand, and so most of the approaches for ship routing problem are not applicable in our problem.

16. Today’s Topic Q & A