Özlem Ergun

Network Design and Allocation Mechanisms for Carrier Alliances in Liner Shipping

Many real-world systems operate in a decentralized manner, where individual operators interact with varying degrees of cooperation and self motive. In this paper, we study transportation networks that operate as an alliance among different carriers. In particular, we study alliance formation among carriers in liner shipping. We address tactical problems such as the design of large-scale networks (that result from integrating the service networks of different carriers in an alliance) and operational problems such as the allocation of limited capacity on a transportation network among the carriers in the alliance. We utilize concepts from mathematical programming and game theory and design a mechanism to guide the carriers in an alliance to pursue an optimal collaborative strategy. The mechanism provides side payments to the carriers, as an added incentive, to motivate them to act in the best interest of the alliance while maximizing their own profits. Our computational results suggest that the mechanism can be used to help carriers form sustainable alliances.

Multi-path selection for multiple description encoded video streaming

This paper presents a new framework for multimedia streaming that integrates the application and network layer functionalities to meet such stringent application requirements as delay and loss. The coordination between these two layers provides more robust media transmission even under severe network conditions. In this framework, a multiple description source coder is used to produce multiple independently-decodable streams that are routed over partially link-disjoint (non-shared) path to combat bursty packet losses. We model multi-path streaming and propose a multi-path streaming and propose a multi-path selection method that chooses a set of paths maximizing the overall quality at the client. Overlay infrastructure is then used to achieve multi-path routing over these selected paths. The simulation results show that the average peak signal-to-noise ratio (PSNR) improves by up to 8.1 dB, if the same source video is routed over intelligently selected multiple paths instead of the shortest path or maximally link-disjoint paths. In addition to PSNR improvement in quality, the end-user experiences a more continual steaming quality.

Pickup and Delivery with Split Loads

Splitting loads such that the delivery of certain loads is completed in multiple trips rather than one trip results in opportunities for a reduction in cost and the number of vehicles used. Several studies have shown the benefit of split deliveries for the vehicle routing problem, in which a vehicle operating out of a depot makes a series of deliveries on each route. In this paper, we quantify the benefit of using split loads for the pickup and delivery problem. A heuristic to solve the pickup and delivery problem with split loads is developed and applied to a set of random large-scale problem instances, revealing the potential benefit of split loads. This benefit is reduced when the heuristic is applied to a real-world trucking industry problem because of several problem instance characteristics. The benefit of split loads is found to be most closely tied to three characteristics: load size, cost associated with a pickup or delivery, and the frequency with which loads have origins or destinations in common. Prior to a discussion of these results, we define the pickup and delivery problem with split loads and prove that for a set of given origins and destinations the most benefit can occur with load sizes just above one half of vehicle capacity.

Very large-scale neighborhood search

One of the central issues in developing neighborhood search techniques is defining the neighborhood. As a rule of thumb, larger neighborhoods contain higher quality local optimal solutions compared to smaller neighborhoods. However, larger neighborhoods also typically require more time to search than smaller neighborhoods. A neighborhood search algorithm is not practical if the neighborhoods cannot be searched efficiently. Thus, a rapid search algorithm is needed to make efficient use of large neighborhoods.

Lane-Exchange Mechanisms for Truckload Carrier Collaboration

Because of historically high fuel prices, the trucking industrys operating expenses are higher than ever and thus profit margins are lower than ever. To cut costs, the trucking industry is searching for and exploring new ideas. We investigate the potential of collaborative opportunities in truckload transportation. When carriers serve transportation requests from many shippers, they may be able to reduce their repositioning costs by exchanging one or more of them. We develop optimization models to determine the maximum benefit that can be derived from collaborating. We also develop various exchange mechanisms which differ in terms of information sharing requirements and side payment options that allow carriers to realize some or all of the costs savings opportunities.

The Maximum Flow Network Interdiction Problem: Valid inequalities, integrality gaps, and approximability

We present two classes of polynomially separable valid inequalities for the Maximum Flow Network Interdiction Problem. We prove that the integrality gap of the standard integer program is not bounded by a constant, even when strengthened by our valid inequalities. Finally, we provide an approximation-factor-preserving reduction from a simpler interdiction problem.

Creating very large scale neighborhoods out of smaller ones by compounding moves

This paper discusses neighborhood search algorithms where the size of the neighborhood is “very large” with respect to the size of the input data. We concentrate on such a very large scale neighborhood (VLSN) search technique based on compounding independent moves (CIM) such as 2-opts, swaps, and insertions. We present a systematic way of creating and searching CIM neighborhoods for routing problems with side constraints. For such problems, the exact search of the CIM neighborhood becomes NP-hard. We introduce a multi-label shortest path algorithm for searching these neighborhoods heuristically. Results of a computational study on the vehicle routing problem with capacity and distance restrictions shows that CIM algorithms are very competitive approaches for solving vehicle routing problems. Overall, the solutions generated by the CIM algorithm have the best performance among the current solution methodologies in terms of percentage deviation from the best-known solutions for large-scale capacitated VRP instances.

A dynamic programming methodology in very large scale neighborhood search applied to the traveling salesman problem

We consider the standard dynamic program to solve the TSP. We then obtain exponentially large neighborhoods by selecting a polynomially bounded number of states, and restricting the dynamic program to those states only. We show how the Balas and Simonetti neighborhood and the insertion dynasearch neighborhood can be viewed in this manner. We also show that one of the dynasearch neighborhoods can be derived directly from the 2-exchange neighborhood using this approach.

Collaboration in Cargo Transportation

We discuss two forms of collaboration in cargo transportation: carrier alliances in sea and air cargo, and shipper collaborations in trucking. After discussing the current industry settings that make such collaborations beneficial, we present a set of questions that need to be answered in the collaborative setting. These questions deal with issues such as (i) what is the maximum benefit the collaboration can achieve? (ii) How should these benefits be allocated? (iii) What membership rules and regulations will increase the sustainability of a given alliance? We provide a set of models for resolving these issues and analyze the properties of the solutions obtained from them.

Mechanism design for a multicommodity flow game in service network alliances

We study a collaborative multicommodity flow game where individual players own capacity on the edges of the network and share this capacity to deliver commodities. We present membership mechanisms, by adopting a rationality based approach using notions from game theory and inverse optimization, to allocate benefits among the players in such a game.