2015 Informs Annual Meeting

SB66

INFORMS Philadelphia – 2015

SB66 66-Room 113C, CC Aviation Applications Section: Best Student Presentation Competition 1 Sponsor: Aviation Applications Sponsored Session

2 - Crowdshipping for Same-day Delivery Niels Agatz, Rotterdam School of Management, Erasmus University, Burgemeester Oudlaan 50, Rotterdam, Netherlands, nagatz@rsm.nl, Alp Arslan Crowdshipping entails obtaining transportation services from approved drivers and carrier companies with spare capacity rather than from traditional logistics partners. The key idea is to exploit unused capacities and existing transportation flows of the crowd to save delivery cost and provide faster delivery. This study investigates the use of crowdshippers for last-mile delivery in a same-day delivery setting. 3 - The Pickup and Delivery Problem with Time Windows, Scheduled Lines and Stochastic Demands This paper concerns scheduling a set of vehicles to serve a set of requests, whose expected demands are known in distribution when planning, but are only revealed with certainty upon vehicles’ arrival. In addition, a part of the transport plan can be carried out on limited-capacity scheduled public transportation lines using bus, train, tram, metro, etc. We present the model, solution approach and numerical results. SB68 68-Room 201B, CC Joint Session TSL/Public Sector: Transportation Issues in Emergency Response Sponsor: Transportation, Science and Logistics & Public Sector Sponsored Session Chair: Kash Barker, Associate Professor, University of Oklahoma, 202 W Boyd St, Rm. 124, Norman, OK, 73019, United States of America, kashbarker@ou.edu 1 - Combining Worst and Average Case Considerations in an Integrated Emergency Response Network Design Jyotirmoy Dalal, Assistant Professor, Indian Institute of Management Udaipur, IIM Udaipur, MLSU Campus, Udaipur, 313001, India, jyotirmoy.dalal@gmail.com, Halit Uster We design an emergency response network, integrating relief (supply) and evacuation (demand) sides under uncertainties in demand amount and location. We formulate a MIP, combining stochastic and robust optimization concepts as the weighted sum of the corresponding objectives. For varying relative weights, we devise alternative approaches to solve large scale problem instances. We present computational result and insights gained by applying the model to a GIS- based case study on coastal Texas. 2 - A Multi-period Dynamic Location Planning Model for Emergency Response Burcu Keskin, Associate Professor, The University of Alabama, 345 Alston Hall, 361 Stadium Drive, Tuscaloosa, AL, 35487, United States of America, bkeskin@cba.ua.edu, Jianing Zhi, Sharif Melouk We propose a deferred service model to analyze the daily operations of ambulances that involve dispatch and redeploy. Given incident priority levels and patterns, we decide which incidents to serve immediately or to defer to following periods while incurring deferral penalty costs. Considering network size, fleet size, incident patterns, and time-dependent parameters, we compare the results in terms of service, response time, and cost through experimentation and offer new dispatch policies. 3 - Replenishment Location Planning for Service Trucks under Network Congestion and Routing Constraints Leila Hajibabai, Clinical Assistant Professor, Washington State University, 405 Spokane St., Sloan 119, P.O. Box 64291, Pullman, WA, 99164, United States of America, leila.hajibabai@wsu.edu It is often challenging to plan service trucks operations under network design constraints, especially on congested roadways. An integrated model is developed to simultaneously determine the optimal location design of replenishment facilities, minimize routing cost in the proposed network, assign traffic, and select candidate links for capacity expansion. A genetic algorithm is proposed that integrates a continuous approximation model for routing cost estimation and traffic assignment algorithm. Tom Van Woensel, Full professor, Eindhoven University of Technology, Den Dolech 2, Eindhoven, NB, Netherlands, t.v.woensel@tue.nl

Chair: Bo Zou, University of Illinois at Chicago, 2095 Engineering Research Facility, 842 W. Taylor Street (M/C 246), Chicago, IL, 60607- 7023, United States of America, bzou@uic.edu 1 - Predicting Airport Arrivals using Data Mining Techniques Sreeta Gorripaty, Student, University of California Berkeley,

116 McLaughlin Hall, UC Berkeley, Berkeley, CA, 94720, United States of America, gorripaty@berkeley.edu, Yi Liu, Alexey Pozdnukhov, Mark Hansen

One way to define similarity between two days in the NAS is measuring the difference in their airport arrival counts. Similar historical days can be extracted by predicting the airport arrivals for a given day and can be subsequently used in decision support tools. In our work, we use machine learning algorithms of support vector regression and random forest to predict the number of arrivals. These models also quantify the contribution of factors such as weather and demand, on airport arrivals. 2 - Airline Alliance and Product Quality: The Case of the U.S. Domestic Airline Industry Jules Yimga, Kansas State University, KS, United States of America, jjules@ksu.edu, Philip Gayle Collusion on price and service levels tends to be the main concern of policymakers when appraising an airline alliance formation. We posit that product quality is an important dimension to be considered in alliance appraisals. This paper investigates the product quality implications of the Delta/Continental/Northwest codeshare alliance with a particular focus on the codeshare effects in markets where the alliance partners competed prior to the alliance. 3 - Statistical Analysis of Dispatcher Fuel Loading Behavior Lei Kang, University of California, Berkeley, 107D McLaughlin Hall, UC Berkeley, Berkeley, Ca, 94720, United States of America, lkang119@gmail.com, Mark Hansen, Megan Ryerson, Lu Hao Airlines are moving aggressively to reduce fuel consumption. Thus, gaining a better understanding of dispatcher fuel loading behavior regarding discretionary fuel (i.e. contingency fuel and alternate fuel) is of great interest to airlines. By combining a large flight level fuel loading dataset with a dispatcher survey provided by a major US airline, dispatcher heterogeneity and its impacts in loading discretionary fuel regarding domestic and international flights will be quantified and compared. Working Towards the Physical Internet Sponsor: TSL/Freight Transportation & Logistics Sponsored Session Chair: Tom Van Woensel, Full Professor, Eindhoven University of Technology, Den Dolech 2, Eindhoven, NB, Netherlands, t.v.woensel@tue.nl 1 - Exploring Operational Problems for Future Delivery Service Operations using Unmanned Aerial Vehicles Heng Chen, University of Massachusetts Amherst, Isenberg School of Management, Amherst, MA, 01003, United States of America, heng@som.umass.edu, Senay Solak It is well accepted that commercial use of UAVs in the near future will involve delivery service operations by retailers and courier companies. We outline some strategic and tactical decisions that these companies will face in UAV based delivery operations, and use currently available data to develop preliminary models for guiding such decisions by a firm. Specifically, optimal policies on certain capacity and revenue management decisions under stochastic demand are studied and derived. SB67 67-Room 201A, CC

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