Randolph W. Hall

Distribution Strategies that Minimize Transportation and Inventory Costs

This paper develops an analytic method for minimizing the cost of distributing freight by truck from a supplier to many customers. It derives formulas for transportation and inventory costs, and determines the optimal trade-off between these costs. The paper analyzes and compares two distribution strategies: direct shipping i.e., shipping separate loads to each customer and peddling i.e., dispatching trucks that deliver items to more than one customer per load. The cost trade-off in each strategy depends on shipment size. Our results indicate that, for direct shipping, the optimal shipment size is given by the economic order quantity EOQ model, while for peddling, the optimal shipment size is a full truck. The peddling cost trade-off also depends on the number of customers included on a peddling route. This trade-off is evaluated analytically and graphically. The focus of this paper is on an analytic approach to solving distribution problems. Explicit formulas are obtained in terms of a few easily measurable parameters. These formulas require the spatial density of customers, rather than the precise locations of every customer. This approach simplifies distribution problems substantially while providing sufficient accuracy for practical applications. It allows cost trade-offs to be evaluated quickly using a hand calculator, avoiding the need for computer algorithms and mathematical programming techniques. It also facilitates sensitivity analyses that indicate how parameter value changes affect costs and operating strategies.

The Fastest Path through a Network with Random Time-Dependent Travel Times

This paper introduces the problem of finding the least expected travel time path between two nodes in a network with travel times that are both random and time-dependent (e.g., a truck, rail, air or bus network). It first shows that standard shortest path algorithms (such as the Dijkstra algorithm) do not find the minimum expected travel time path on such a network, then proposes a method which does find the minimum path. Next, this paper shows that the optimal “route choice” is not a simple path but an adaptive decision rule. The best route from any given node to the final destination depends on the arrival time at that node. Because the arrival time is not known before departing the origin, a better route can be selected by deferring the final choice until later nodes are reached. A method for finding the optimal adaptive decision rule is proposed.

HANDBOOK OF TRANSPORTATION SCIENCE.

Preface to the Second Edition. 1. Transport Science R.W. Hall. Human Elements in Transportation. 2. Discrete Choice Methods and Their Application to Short Term Travel Decisions M. Ben-Akiva, M. Bierlaire. 3. Activity-Based Modelling of Travel Demand C.R. Bhat, F.S. Koppelman. 4. Transportation Safety L. Evans. Flows and Congestion. 5. Transportation Queueing R.W. Hall. 6. Traffic Flow and Capacity M.J. Cassidy. 7. Automated Vehicle Control P. Ioannou, A. Bose 8. Traffic Control M. Papageorgiou. Spatial Models. 9. Continuous Space Modeling T. Puu, M. Beckmann. 10. Location Models in Transportation M.D. Daskin, S.H. Owen. Routing and Network Models. 11. Network Equilibrium and Pricing M. Florian, D. Hearn. 12. Street Routing and Scheduling Problems L. Bodin, et al. 13. Long-haul Freight Transportation T.G. Crainic. 14. Crew Scheduling C. Barnhart, et al. 15. Supply Chains R. Hall. Economic Models. 16. Revenue Management G.van Ryzin, K. Talluri. 17. Spatial Interaction Models P. Rietveld, P. Nijkamp. 18. Transport Economics R. Arnott, M. Kraus. Biographies. Index.

DISTANCE APPROXIMATIONS FOR ROUTING MANUAL PICKERS IN A WAREHOUSE

This paper evaluates and compares strategies for routing a manual picker through a simple warehouse. It expands on previous work, in which optimization algorithms were developed, by deriving equations which relate route length to warehouse attributes. Several rules of thumb are derived for selection of order picking strategies and optimization of warehouse shape.

BUS DISPATCHING AT TIMED TRANSFER TRANSIT STATIONS USING BUS TRACKING TECHNOLOGY

A timed transfer terminal synchronizes the arrival of incoming vehicles with the departure of outgoing vehicles so as to minimize transfer delays. Most bus timed transfer terminals follow fixed schedules, and do not utilize intelligent transportation systems for vehicle tracking and control. This paper reviews technologies that enable real-time control of timed transfer. We evaluate the benefits of tracking bus locations and executing dynamic schedule control through the simulation of a generic timed transfer terminal under a range of conditions. Based on empirical data collected by the Los Angeles County/Metropolitan Transit Agency, we found delay over segments of long-headway bus lines to be negatively correlated with lateness at the start of the segment, indicating that buses have a tendency to catch up when they fall behind schedule. The simulation analysis showed that the benefit of bus tracking is most significant when one of the buses experiences a major delay, especially when there is a small number of connecting buses.

Travel outcome and performance: The effect of uncertainty on accessibility

An accessibility model is a conceptual tool which explains the interdependencies between the transportation infrastructure and human activities. Traditionally, theorists have based their accessibility models upon deterministic approximations. However, uncertainty in itself can affect whether an activity is accessible, and affect how one measures accessibility. In the first section of this paper, it is shown that travel time randomness interacts with the scheduling of human activities to define the region which is accessible to a traveler. In the second section, a problem is considered where a traveler must search among opportunities to locate a certain activity he desires. It is found that there exists an optimal cluster size which minimizes travel cost, the size being a decreasing function of the probability of locating the activity at any single opportunity.

REAL-TIME CONTROL OF BUSES FOR SCHEDULE COORDINATION AT A TERMINAL

Recently, bus transit operators have begun to adopt technologies that enable bus locations to be tracked from a central location in real-time. Combined with other technologies, such as automated passenger counting and wireless communication, it is now feasible for these operators to execute a variety of real-time strategies for coordinating the movement of buses along their routes. This paper compares control strategies that depend on technologies for communication, tracking and passenger counting, to those that depend solely on local information (e.g., time that a bus arrived at a stop, and whether other connecting buses have also arrived). We also develop methods to forecast bus arrival times, which are most accurate for lines with long headways, as is usually the case in timed transfer systems. These methods are tested in simulations, which demonstrate that technology is most advantageous when the schedule slack is close to zero, when the headway is large, and when there are many connecting buses.

NON-RECURRENT CONGESTION: HOW BIG IS THE PROBLEM? ARE TRAVELER INFORMATION SYSTEMS THE SOLUTION?

Recent research on highway congestion has calculated that over 50% of delays are non-recurrent (incident produced). A common inference seems to be that non-recurrent delay constitutes over 50% of the “congestion problem.” But this inference overlooks the fact that non-recurrent delays would not be nearly as large if highways were not already overloaded, and that as travelers respond to changes in non-recurrent delay, additional demand could significantly reduce the percentage gain. Within this paper, the issue of incident delay is examined from the alternative perspective of “effective capacity” (which will be equivalent to the expected capacity over time). When evaluated from this view, strategies aimed at alleviating peak-period, incident-caused congestion (such as Incident Management, IM, and Advanced-Traveler-Information-Systems, ATIS) have only a marginal long-term effect on the average delay of congested highways. The conclusion is that neither ATIS nor IM can be relied on as the solution to peak-period congestion. It is also unrealistic to consider either ATIS or IM as an effective alternative to the conventional strategy of adding lanes and building highways.

CONFIGURATION OF AN OVERNIGHT PACKAGE AIR NETWORK

The advent and growth of the overnight package industry has been one of the most dramatic changes in North American transportation over the last 10 years. This paper examines the impact of overnight restrictions and time zones on the configuration of an air freight network. The location of a hub terminal impacts the arrival pattern of airplanes at the terminal. For locations to the east of center, arrivals are spread over a longer time span than for locations to the west of center. This allows shipments to be delivered within a short time window without as large investments in sorting equipment. The impact of overnight restrictions on multiple terminal networks is also examined.

Territory Planning and Vehicle Dispatching with Driver Learning

This paper investigates the construction of routes for local delivery of packages. The primary objective of this research is to provide realistic models to optimize vehicle dispatching when customer locations and demands vary from day to day while maintaining driver familiarity with their service territories, hence dispatch consistency. The objective of increasing driver familiarity tends to make routes or service territories fixed. On the other hand, to serve varying demand it is advantageous to reassign vehicles/drivers and service territories each day. To balance the trade-offs between these two objectives, we developed the concepts of “cell,” “core area,” and “flex zone,” and created a two-stage vehicle routing model---strategic core area design and operational cell routing---and explicitly evaluated the effect of driver familiarity through the use of learning and forgetting curves.