The robust single machine scheduling problem with uncertain release and processing times

In this work, we study the single machine scheduling problem with uncertain release times and processing times of jobs. We adopt a robust scheduling approach, in which the measure of robustness to be minimized for a given sequence of jobs is the worst-case objective function value from the set of all possible realizations of release and processing times. The objective function value is the total flow time of all jobs. We discuss some important properties of robust schedules for zero and non-zero release times, and illustrate the added complexity in robust scheduling given non-zero release times. We propose heuristics based on variable neighborhood search and iterated local search to solve the problem and generate robust schedules. The algorithms are tested and their solution performance is compared with optimal solutions or lower bounds through numerical experiments based on synthetic data

Managing inventory in global supply chains facing port-of-entry disruption risks

Ports-of-entry are critical components of the modern international supply chain infrastructure, particularly container seaports and airfreight hubs. The potential operational and economic impact resulting from their temporary closure is unknown, but is widely believed to be very significant. This paper investigates one aspect of this potential impact, focusing specifically on the use of supply chain inventory as a risk mitigation strategy for a one supplier, one customer system in which goods are transported through a port-of-entry subject to temporary closures. Closure likelihood and duration are modeled using a completely observed, exogenous Markov chain. Order lead times are dependent on the status of the port-of-entry, including potential congestion backlogs of unprocessed work. An infinite-horizon, periodic-review inventory control model is developed to determine the optimal average cost ordering policies under linear ordering costs with backlogged demand. When congestion is negligible, the optimal policy is state invariant. In the more complex case of non-negligible congestion, this result no longer holds. For studied scenarios, numerical results indicate that operating margins may decrease 10% for reasonable-length port-of-entry closures, that margins may be eliminated completely without contingency plans, and expected holding and penalty costs may increase 20% for anticipated increases in port-of-entry utilization

Sustainable Passenger Transportation: Dynamic Ride-Sharing

Ride-share systems, which aim to bring together travelers with similar itineraries and time schedules, may provide significant societal and environmental benefits by reducing the number of cars used for personal travel and improving the utilization of available seat capacity. Effective and efficient optimization technology that matches drivers and riders in real-time is one of the necessary components for a successful ride-share system. We formally define dynamic ride-sharing and outline the optimization challenges that arise when developing technology to support ride-sharing. We hope that this paper will encourage more research by the transportation science and logistics community in this exciting, emerging area of public transportation

Stable Matching for Dynamic Ride-sharing Systems

Dynamic ride-sharing systems enable people to share rides and increase the efficiency of urban transportation by connecting riders and drivers on short notice. Automated systems that establish ride-share matches with minimal input from participants provide the most convenience and the most potential for system-wide performance improvement, such as reduction in total vehicle-miles traveled. Indeed, such systems may be designed to match riders and drivers to maximize system performance improvement. However, system-optimal matches may not provide the maximum benefit to each individual participant. In this paper we consider a notion of stability for ride-share matches and present several mathematical programming methods to establish stable or nearly-stable matches, where we note that ride-share matching optimization is performed over time with incomplete information. Our numerical experiments using travel demand data for the metropolitan Atlanta region show that we can significantly increase the stability of ride-share matching solutions at the cost of only a small degradation in system-wide performance

The Value of Optimization in Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta

Smartphone technology enables dynamic ride-sharing systems that bring together people with similar itineraries and time schedules to share rides on short-notice. This paper considers the problem of matching drivers and riders in this dynamic setting. We develop optimization-based approaches that aim at minimizing the total system-wide vehicle miles and individual travel costs. To assess the merits of our methods we present a simulation study based on 2008 travel demand data from metropolitan Atlanta. The simulation results indicate that the use of sophisticated optimization methods instead of simple greedy matching rules may substantially improve the performance of ride-sharing systems. Furthermore, even with relatively low participation rates, it appears that sustainable populations of dynamic ride-sharing participants may be possible even in relatively sprawling urban areas with many employment centers

Stochastic Vehicle Routing with Recourse

We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage optimization problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand instantiations, a recourse route is computed -- but costs here become more expensive by a factor lambda. We present an O(log^2 n log(n lambda))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular orienteering, called knapsack rank-function orienteering. We also give a better approximation ratio for knapsack rank-function orienteering than what follows from prior work. Finally, we provide a Unique Games Conjecture based omega(1) hardness of approximation for StochVRP, even on star-like metrics on which our algorithm achieves a logarithmic approximation.Comment: 20 Pages, 1 figure Revision corrects the statement and proof of Theorem 1.

Chat-Room Voices of Divorced Non-Residential Fathers

This study uses postings by divorced fathers to an unmoderated Internet chat room to sound and analyze their voices. The findings show that the posters expressed an acute sense of powerlessness with respect to their status as non-residential fathers, the imposition of child support, the mothers of their children, the family courts, and lawyers and helping professionals. Although most of their grievances have already been reported in the literature on non-custodial post-divorce parenting, the anonymous postings allow us to hear an intensity of feeling that comes through much more faintly in studies based on interviews or focus groups. Since the posters seem to be a particularly aggrieved and angry group of men who are unlikely to seek professional counseling, the authors suggest professional intervention via the Internet. The challenges that chat room data poses to research are noted

Motor Carrier Service Network Design

This chapter introduces service network design (SND) operations research models and solution methodologies specifically focused on problems that arise in the planning of operations in the trucking, or motor freight, industry. Consolidation carriers such as less-than-truckload and package trucking companies face flow planning problems to decide how to route freight between transfer terminals, and load planning problems to decide how to consolidate shipments into trailerloads and containerloads for dispatch. Integer programming models are introduced for these network design decision problems as well as exact and heuristic solution methods

Evaluation of an expanded satellite based mobile communications tracking system

Since the terrorist events in the United States on September 11, 2001, the Federal Motor Carrier Safety Administration has been testing and evaluating cargo tracking technologies to improve the safety, security, and efficiency of commercial motor vehicle operations. While satellite-based systems used for tracking vehicles and cargo provide sufficient geographic coverage in the majority of the United States, there remain several vital regions that are uncovered and difficult to monitor. One such region is Alaska, where officials arc particularly concerned with the hazardous materials shipments that are transported parallel to the Trans-Alaska Pipeline. This article analyzes the risks and benefits associated with adopting an Expanded Satellite-Based Mobile Communications Tracking System to monitor hazardous materials and high-value cargo in Alaska. Technical and acceptance risks are evaluated against the communication, safety, security and real time information benefits that the system provides. The findings indicate that the system provides a significant communications upgrade relative to previously available technology