Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

SC30

Lean Six Sigma, Decision Models, and Risk Management will show how to proctor online exams, grade handwritten homework, automatically grade custom assignments, and manage the online process.

n SC30 North Bldg 221C Innovations in Facility Logistics – Technology and Models Sponsored: TSL/Facility Logistics Sponsored Session Chair: Debjit Roy, Indian Institute of Management, Ahmedabad, 560078, India 1 - Dynamic Batch Picking for Order Picking in Warehouses Jelmer Pier van der Gaast, University of Groningen, Nettelbosje 2, Groningen, 9747 AE, Netherlands, Bolor Jargalsaikhan, K.J. Roodbergen Dynamic batch picking is characterized by combining product demand from multiple customer orders into one pick tour where new orders arrive continuously. Using modern order picking aids, updated pick instructions can be included in the current pick tours which allows pickers to be re-routed to pick for new orders even when they already started a pick tour. We develop a mathematical model for dynamic batch picking that minimizes the order throughput time of an incoming order. The model can be quickly re-optimized in case of a new order arrival and used to determine new updated pick tours. This allows for short order throughput times and ensures that companies can set their cut-off times as late as possible. 2 - The Effects of Hurricanes on Port Operations This paper studies the long-lasting effects of hurricanes on port operations. It focuses on the recent effect of hurricane Harvey on the Port of Houston. Hurricane Harvey pushed a large amount of sediment into the Houston Ship Channel, decreasing the depth of the port. As a result, larger vessels need to de- ballast the water from the ballast tanks in order to reduce their draft and enter the port. Arena simulation software is used to simulate the operations at the two main container terminals in the port. Two simulations are created to model the port and its efficiency before Harvey versus after Harvey. The results show a decrease of total revenue and an increase in average waiting time. 3 - Manual Order Picking in a Warehouse Ivo Adan, Eindhoven University of Technology, Den Dolech 2, Eindhoven, 5600 MB, Netherlands, Lacy Greening, Rob Broekmeulen, Stijn De Vuyst We consider manual order-picking in a rectangular warehouse consisting of multiple parallel aisles. The routing heuristic of the picker is the mid-point strategy. We determine mean and variance of the travel time and also evaluate the performance of batching strategies. 4 - Stochastic Models for Comparing Technology Alternatives at Automated Container Terminals Govind Lal Kumawat, Indian Institute of Management Ahmedabad, New Campus, Dorm 29 Room 12, Ahmedabad, 380015, India, Debjit Roy We address a technology selection problem that arises in the development phase of automated container terminals. We compare various technology alternatives for quay cranes and transport vehicles based on the throughput time using semi- open queuing networks. Moreover, we propose a solution method for semi-open queuing networks with two-phase servers and blocking. 5 - Workforce Scheduling with Order Picking Assignments in Distribution Facilities Arpan Rijal, Erasmus University, Postbus 1738, Rotterdam, 3062PA, Netherlands, Marco Bijvank, Asvin Goel, René de Koster Manual order picking operations at several distribution centers operate with temporal restrictions on the completion times of orders in the form of hard earliness or lateness constraints. The problem is further complicated by multiple shift start and end times, mandatory breaks, and flexible workforce. As a result, the sequence of assignment of orders to order pickers is non-trivial. In this work, we present several formulations of the problem and exact and matheuristic solution approaches for it. Preliminary results show that definition of shifts and break requirements have significant impact on operational costs. Amir Gharehgozli, David Nazarian College of Business and Economics, Northridge, CA, United States, Dylan Folkman

n SC28 North Bldg 221A Railway Applications Section Problem Solving Competition Sponsored: Railway Applications Sponsored Session Chair: Michael F. Gorman, University of Dayton, Dayton, OH, 45469, United States 1 - Railway Applications Section Problem Solving Competition Michael F. Gorman, University of Dayton, 300 College Park, Dayton, OH, 45469, United States This session is reserved for the finalists of the RAS Problem Solving Competition: “Train Delay Forecasting” The presenters and their abstracts will be determined the Judging Committee by early October. More information about the Competition is available at http://connect.informs.org/railway- applications/awards/problem-solving-competition. n SC29 North Bldg 221B Cooperative Traffic Sponsored: TSL/Urban Transportation Sponsored Session Chair: Daisik Nam, University of California, 2132 Verano Place, Irvine, CA, 92617, United States 1 - Nash Equilibrium with User-Focused Incentives for Envy-minimized Daisik Nam, University of California, 2132 Verano Place, Irvine, CA, 92617, United States This research models an incentivized and interconnected smart route guidance system. The system provides the users with system optimum routes, which distributes travel demands over space and time but induces travel time imbalances and user envy. To compensate for this, optimum incentives are allocated, that attempt to minimize the envy of participants. 2 - Economic Mechanisms for Cooperative Vehicle Platooning Xiaotong Sun, University of Michigan, Department of Civil and Environmental Enginee, Ann Arbor, MI, 48109, United States, Yafeng Yin A vehicle platoon is a set of vehicles driving together with minimum headways, enabled by, e.g., cooperative adaptive cruise control. Benefits of vehicle platooning include energy cost savings, reduced emissions, and others. Since these benefits are not distributed evenly among vehicles in a platoon, somedrivers or owners will not be willing to join or stay in a platoon even if they are advised to do so. This study investigates economic mechanisms that fairly allocate the platoon benefits to facilitate vehicles from different owners to form and maintain desired platoons. 3 - Decentralized Cooperative Control for a Mixed Flow Traffic Platoon Yujie Li, Purdue University, West Lafayette, IN, United States This study develops a cooperative control strategy for a platoon with human- driven vehicles (HDVs) and connected and autonomous vehicles (CAVs) on a straight highway to improve the stability of the whole platoon. Specifically, a novel car-following model for HDVs is established to describe the interactions when a HDV follows a CAV. A cooperative decentralized controller is proposed to generate the control inputs of CAVs by considering the interactions between HDVs and CAVs and the performance of the mixed flow platoon. Numerical simulations are used to investigate the performance of the proposed methodology. 4 - Cooperative Adaptive Cruise Control for a Platoon of Connected and Autonomous Vehicles (CAVs)Considering Dynamic Information Flow Topology Anye Zhou, Purdue University, West Lafayette, IN, United States This study seeks to establish a cooperative adaptive cruise control design that considers a dynamic information flow topology for CAV platoons. This mechanism aims to improve the control performance considerably under an unreliable vehicle-to-vehicle communication network. An adaptive Proportional-Derivative (PD) controller under a two-predecessor-following information flow topology is proposed to reduce the negative effects when communication failures occur. The PD controller parameters are determined to ensure the head-to-tail string stability of the CAV platoon.

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