Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

SB31

2 - A Two-sided Ride-sharing Optimization Problem Considering Electric Vehicle Deployment Sang Jin Kweon, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, United States Ride-sharing platforms are online mobile platforms which match riders with drivers. As electric vehicles receive attention, the ride-hailing giant has dabbled in electric vehicle programs. In this talk, we address the ride-sharing problem to analyze the impacts of electric vehicle deployment on ride-sharing systems. A two-sided model for ride-sharing systems is formulated, and the closed-form solution is derived to maximize the ride-sharing platform’s operating profitability. The numerical results are further discussed to quantify the impacts of deployment and utilization of electrified fleets in urban transportation systems. 3 - Evaluating and Optimizing Charging Strategies for Electrical Busses in Public Transportation Networks Pieter van den Berg, Rotterdam School of Management, Erasmus University, Burgemeester Oudlaan 50, Rotterdam, 3062 PA, Netherlands, Ayman Abdelwahed, Tobias Brandt, John Collins, Wolfgang Ketter, Wolfgang Ketter Public transport operators increasingly face a challenging problem in switching from conventional diesel to electrical busses. Cooperating with the public transport operator in the city of Rotterdam, we develop a discrete-event-based simulator to study the scheduling feasibility by applying different charging strategies. Some fundamental strategies are assessed such as “first in first served and “lowest charge highest priorityö. A mixed integer linear programming optimization model is then introduced to obtain the optimal charging strategy, which showed better results. n SB30 North Bldg 221C Collaborative and Flexible Logistics Sponsored: TSL/Facility Logistics Sponsored Session Chair: Jennifer A. Pazour, Rensselaer Polytechnic Institute, Troy, NY, 12180, United States 1 - Towards a Collaborative Supply Chain: A Quantitative Approach to Shared Facility Design and Operations Chase Rainwater, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR, 72701, United States, Kimberly P. Ellis, William G. Ferrell, Philip Kaminsky Supply chain experts agree that goods will move more quickly, require more customization, and be shipped to a more urbanized customer base over the next 25 years. The current logistics system makes inefficient use of transportation and storage resources. One answer to this growing problem is the adoption of a collaborative logistics system in which manufacturers, transporters, distributors and retailers make use of shared resources. This talk focuses specifically on how collaborative use of facilities should be approached operationally. A mathematical program is presented with results highlighting the differences in system operations from that seen in current logistics systems. 2 - Performance Analysis of Modern Goods-to-person Order Picking Systems Francisco Jose Aldarondo, University of Michigan, 3512 Green Brier Boulevard, Apartment 497C, Ann Arbor, MI, 48105, United States For many online retailers, order picking (OP) is a labor-intensive activity, and it typically accounts for over 50% of their operational costs. Although many online retailers use walk-and-pick systems, a stronger alternative is goods-to-person OP, which generally improves the picker efficiency and offers ergonomic advantages. In such systems, automated equipment brings the containers to the pick station(s) where picker(s) perform the picks. In this study, we are concerned with the performance analysis of state of the art good-to-person systems and the operational challenges they present. 3 - Flexible Supply Chain Network Design with Different Granularity Options Kaan Unnu, Rensselaer Polytechnic Institute, Center For Industrial Innovation, 110 8th Street, Troy, NY, 12180-3590, United States, Jennifer A. Pazour On-demand distribution matches underutilized capacity to entities who need distribution services on-demand. This enables finer commitment and capacity granularities, creates flexibility to address demand variability and volatility, but has higher variable costs. Our multi-period capacitated facility location problem simultaneously decides the best combination of distribution options (construction, long-term lease or on-demand). The proposed heuristic algorithm, combining p- median, decomposition, and column generation, is used to solve different scenarios and provide managerial insights.

n SB31 North Bldg 222A

Advances in Routing and Network Algorithms Sponsored: TSL/Intelligent Transportation Systems (ITS) Sponsored Session Chair: Mohamad Kamal El Din Ahmad Hasan, Kuwait University, Department of Quantitative Methods &IS, CBA, Kuwait City, 13055, Kuwait 1 - Mean-standard Deviation Model for Capturing Reliability in the Minimum Cost Flow Problem Can Gokalp, University of Texas, Austin, TX, United States, Stephen D. Boyles We study the mean-standard deviation network flow problem, where the objective is minimizing a linear combination of the mean and standard deviation of path costs. This optimization problem is non-linear and non-additive. We prove that the efficient frontier of this problem is a subset of the efficient frontier of the mean-variance problem. Leveraging this result we provide an algorithm that solves this problem by solving an easier mean-variance problem. 2 - Routing in Time-dependent Networks: A Microstate Interpretation of Dynamic Traffic Assignment Mohammad Arani, PhD candidate, University of Arkansas, 7005 Archwood Dr., Little Rock, AR, 72204, United States, Yupo Chan Dynamic traffic assignment suggests that, for the same origin and destination pair, a driver who departs later may reach her destination ahead of those who depart earlier. Although this has been shown, the result may be heavily dependent on the characteristics of a traffic network. Consider a directed graph G (N, A), where the travel time and reliability of a commuting path varies over the day. For a risk- averse and a risk-prone driver, we wish to study the driver’s behavior regarding different metrics. Included in the study is the ability for a driver to not only defer her departure time but also wait en-route for the traffic to clear. A computational study has been conducted on Central Arkansas network. 3 - Steep Roads Impact on Vehicle Routing Decisions Ricardo Giesen, Associate Professor, Universidad Catolica de Chile, Vicuna Mackenna 4860 Macul, Casilla 306 Cod. 105, Santiago, Chile, Mathias A. Klapp, Carlos Brunner Most routing decisions assume that the world is flat, however there are many cities in which this assumption does not hold. Thus, we formulated a Vehicle Routing Problem in regions with steep roads (VRP-sr), and implemented a heuristic solution method for this problem. We use this model to study the impacts of not taking into account steep road grades when routing vehicles which are visiting customers located at point with differences in altitude. Our initial results, show that in hilly cities cost reductions between 3% to 6% on average can be obtained when taking into account steep road grades. Moreover, there are instances in which cost reduction greater than 14% can be achieved. 4 - Online Routing of Heterogeneous Vehicles on Stochastic Time-Varying Managed Lane Networks Priyadarshan Patil, University of Texas-Austin, 301 E. Dean Keeton Street, Stop C1761, Austin, TX, 78712, United States, Venktesh Pandey, Stephen D. Boyles Managed lane (ML) networks have multiple entrances and exits, complicating the route choice decisions of travelers. Current algorithms in the literature either assume that travelers only compare a subset of alternatives or assume a value of time distribution which is difficult to calibrate. This presentation describes efficient algorithms exploiting the acyclic nature of the ML networks for optimal routing of vehicles given stochastic variation of toll and travel time values. We compare the performance of the algorithm against other methods and on larger networks. 5 - A Link Node Nonlinear Complementarity Model for a Multiclass Simultaneous Transportation Dynamic User Equilibria Mohamad Kamal El Din Ahmad Hasan, Professor of Operations and Supply Chain Managemen, Kuwait University, Department of Quantitative Methods & Information Systems, College of Business Administration, Kuwait City, 13055, Kuwait, Xuegang Ban In this paper, the authors combine a dynamic link-node based discrete-time Nonlinear Complementarity Problem (NCP) Dynamic Traffic Assignment (DTA) model with a static Multiclass Simultaneous Transportation Equilibrium Model (MSTEM) in a unified dynamic link-node based discrete-time NCP Dynamic Multiclass Simultaneous Transportation Equilibrium Model (DMSTEM) model. The new model improves the prediction process and eliminates inconsistencies that arise when the DTA or Dynamic Traffic Assignment with Departure Time (DTA-DT) is embedded in a more comprehensive transportation planning framework. An iterative solution algorithm for the proposed DMSTEM model is proposed.

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