An intermodal multicommodity routing problem with scheduled services

We study a multicommodity routing problem faced by an intermodal service operator that uses ground and maritime transportation. Given a planning horizon, a set of commodities to be picked up at their release times and to be delivered not later than their duedates, the problem is to decide on routes for these commodities using trucks and scheduled and capacitated maritime services at minimum cost of transportation and stocking at the seaports. Two mixed integer programming formulations and valid inequalities are proposed for this problem. The results of a computational study to evaluate the strength of the linear programming relaxations and the solution times are reported. © 2011 Springer Science+Business Media, LLC

Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem

Scheduled service network design with synchronization and transshipment constraints for intermodal container transportation networks

In this paper we address the problem of scheduled service network design for container freight distribution along rivers, canals, and coastlines. We propose a new concise continuous- time mixed-integer linear programming model that accurately evaluates the time of occurrence of transportation events and the number of containers transshipped between vehicles. Given the transportation network, the eet of available vehicles, the demand and the supply of containers, the sailing time of vehicles, and the structure of costs, the objective of the model is to build a minimum cost service network design and container distribution plan that denes services, their departure and arrival times, as well as vehicle and container routing. The model is solved with a commercial solver and is tested on data instances inspired from real-world problems encountered by EU carrier companies. The results of the computational study show that in scheduled service networks direct routes happen more often when either the eet capacity is tight or the handling costs and the lead time interval increase. The increase of the same parameters leads to the decrease of the number of containers transshipped between vehicles

Multimodal multicommodity routing problem with scheduled services

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2008.Thesis (Master's) -- Bilkent University, 2008.Includes bibliographical references leaves 56-58.We study a multicommodity network flow problem faced by a third party logistics company that has the possibility of using ground and maritime transportation. We are given a set of commodities which should be picked up from their origins at given release times and should be delivered to their destinations no later than their duedates. The commodities may be carried directly from their origins to their destinations on trucks, or they may be carried on trucks to a seaport, may visit several seaports using maritime services, and then to be carried to their destinations on trucks. There is no capacity and time limitation on the use of ground transportation. However, the maritime services are scheduled in advance and the company has limitations on the amounts of volume that it can use on each service. The aim is to determine routes for commodities in order to minimize the sum of transportation cost and stocking costs at seaports, respecting the capacity and time related constraints. We call this problem the “Multimodal Multicommodity Routing Problem with Scheduled Services (MMR-S)”. We first prove that the problem is NP-hard. Next, we propose a first mixed integer programming formulation and strengthen it using variable fixing and valid inequalities. We relax the capacity constraints in a Lagrangian manner and show that the relaxed problems decompose into a series of shortest path problems defined on networks augmented by time for each commodity. The corresponding Lagrangian dual yields a lower bound, which may be stronger than that of the linear programming relaxation of our first formulation. Then, we provide an extended formulation whose linear programming relaxation gives the same bound as the Lagrangian dual. Finally, we use the Lagrangian relaxation to devise heuristic methods and report the results of our computational study.Ayar, BurakM.S

Managing heterogeneous traffic on rail freight networks incorporating the logistics needs of market segments

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1994.Includes bibliographical references (leaves 203-209).by Oh Kyoung Kwon.Ph.D

Multi-carrier track capacity allocation in forward and spot markets of freight transport

This dissertation addresses multi-carrier, multi-line train scheduling problems for forward and spot markets. Schedules resulting from solution of these train scheduling problems enable carriers to make customer commitments for serving forward contracts and to transport one-off-loads arising on spot markets. A train slot selection model based on multicommodity network flow concepts is developed for determining timetables for use in forward markets and a column generation methodology is proposed for its solution. The model considers needs of both shippers and carriers. The solution approach is embedded in a simulation-based iterative framework, where demand elasticity is explicitly treated. A combinatorial auction-based track capacity allocation framework is introduced to allocate residual track capacity among competing carriers seeking to run additional trains on an as-needed basis. Bid set construction techniques are proposed that allow carriers to express their preferences for track usage. A winner determination problem is formulated, solution of which provides the optimal allocation of track capacity among carriers. The potential benefits of collaborative operation among carriers in both markets were recognized. Collaborative decision-making (CDM) strategies are designed for scheduling trains to serve forward markets. Performances of these strategies are assessed in a carrier collaboration simulation-assignment framework. A train space leasing technique and a CA-based train slot creation approach are proposed to accommodate one-off-loads on previously scheduled and newly formed trains, respectively. Required techniques for bid set construction are developed. A WDP is formulated that seeks the optimal allocation of track access rights to bidders for the given bid sets. Implementation of the resulting train schedules will aid in creating efficient and cost-effective rail transport, resulting in a competitive and green alternative to truck transportation. Additionally, collaboration among competing carriers can lead to the formation of profitable trains that might otherwise have been underutilized and an ability of each carrier to serve a greater share of the freight market. The methodologies were specifically intended for solving large, real-world train scheduling problems

A chance-constrained stochastic approach to intermodal container routing problems

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost