Research Projects by Dr. Ali Haghani

Dynamic Decision Making for Less-Than-Truckload Trucking Operations
Dr. Ali Haghani and Behrang Hejazi, Ph.D. Candidate

Among different modes of transportation, trucking remains the shipping choice for many businesses and is increasing its market share. Less-than-truckload (LTL) trucking companies provide consolidated transportation, where several customers are served simultaneously by using the same truck, and shipments need to be consolidated at some terminals to build economical loads.

Intelligent transportation system (ITS) technologies offer the possibility to control the operations in real-time. Prior research efforts have considered real-time acceptance/rejection of shipping requests, but mostly have focused on truckload trucking operations.
This study attempts to use real-time information in decision making for LTL carriers in the dynamic environment.

The research presents a mathematical formulation for the problem. A decision making procedure, as well as a decision support application have been developed, which is used to handle the LTL shipment requests. Using exact methods to solve the MIP problem the execution time grows quickly with problem size. Our next step in this study is to introduce alternative methods and algorithms to solve the MIP problem.

Container Ship Stowage Planning with Quay Crane Utilization
Dr. Ali Haghani and Masoud Hamedi, Ph.D. Candidate

Because of higher competition among ports in recent years, improving the efficiency has become an important issue in containership operations. One of the measures of performance is berthing time at port which is determined by the arrangement of containers both within the container terminal and on the containership. Most of the berthing time of a containership consists of unloading and loading time of containers. Determining an efficient configuration of containers that facilitates this process is an everyday problem solved by ship planners.

This research deals with the containership stowage planning problem which is the problem of stacking containers on different bays of a containership that visits several ports during a voyage. Containers may have difference types, sizes, weights and destinations. At each port quay cranes unload the import containers from and load the export containers onto the ship. Since the stacks are accessible only from the top, for unloading an individual container all the containers on top of it must be unloaded first. If the top containers have a different destination they must be loaded back onto the ship. Each of these extra movements is called a shift or re-handling which increases both the operational cost and ship turnaround time. In addition to that if the distribution of containers among the bays matches the configuration of available quay cranes at each port, the cranes can operate on the ship more efficiently. The stability of the containership must be retained during the voyage.
A methematical optimization framework is developed to solve the problem. Since the problem is NP-Complete, heuristics are needed to deal with real world cases.

Every two weeks, Office of Real Estate (ORE) receives around 1,500 requests for information related to plats from SHA customers. It is estimated that about 25% of them are internal and the remaining 75% are external requests. Presently the retrieval process of the required plats is purely human-driven. In order to query for the right ones, the plats have to be manually retrieved according to their numbers out of more than 60,000 available plats. The process is therefore very time-consuming and error-prone and the turnaround time is very long. This has been a persistent problem for years.

The objective of this research project was to develop a prototype automated computerized system to perform queries on an existing right-of-way plat database. The system offers user-friendly interactive map-based interface. The system is specially designed to minimize organizational impact and eliminate the time-consuming manual query to the extent possible. All requests to the ORE related to plat database will be replied quickly as long as the query area is covered by plats that are in the database. In addition, the system is designed so that it can be further developed to serve network user, intranet-based users and internet-based user.

Optimal Scheduling of Evacuation Operations
Dr. Ali Haghani and Abbas M. Afshar, Ph.D. Candidate

Evacuation Planning and Emergency Management is a sophisticated field of civil engineering sciences, aimed to save human lives by safe facility design and optimization of evacuation and rescue operations. Demand estimation, behavioral analysis, destination selection, and route selection are 4 steps of evacuation planning required before the actual plan set up and implementation. Recent approaches advertise integration of last 3 steps to achieve system optimal plans.

Mathematical formulation, traffic simulation and optimization algorithms are required components of such approaches.
In this research, an optimization model for Emergency Evacuation Planning is proposed along with a simulation-optimization framework to solve for the system optimal evacuation plan. The model simultaneously solves for the choice of destination (shelter), evacuation route, and departure time for all evacuees from given origins (endangered zones).

Heuristic algorithms are proposed to find the system-optimal Dynamic Traffic Assignment during an iterative procedure. The mesoscopic traffic simulator is embedded in the optimization modules to find travel time marginals and obtain required performance measures in each iteration.

For the case study of Ocean city in Maryland, implementing the proposed solutions shows dramatic improvements in network performance measures such as total travel time and network clearance time.

*Map source: http://oceancity.umd.edu