Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

WC30

3 - Coordination, Information Sharing, and Return Variabilities in Closed-loop Supply Chains Juan Pedro Sepulveda-Rojas, Associate Professor, University of Santiago of Chile, Avda Ecuador 3769, Santiago de Chile, Chile We analyze quantitatively coordination, information sharing and return variabilities in a closed-loop supply chain context. We evaluate the value of coordination for operational decisions (in the context of inventory management decisions). One of the more important characteristics of the closed-loop supply chain context is the addition of uncertainties about returns. Thus, this work is focused on coordination problems imposed by the flows of returned products. In particular, we want to analyze if the gains expressed in the literature remains, decrease or increase in presence of coordination, return variability and information sharing among the actors of the supply chain. 4 - Product Recovery Decision-making in the Context of Internet of Things: A Review and Generic Roadmap to End-of-life Product Management Xianghui (Richard) Peng, Penn State Erie, The Behrend College, Erie, PA, United States, Kai Meng, Ying Cao, Victor R. Prybutok This research provides a state of the art review on End-of-Life (EOL) product recovery decision-making in the context of Internet of Things. We contextualize and apply an implementation framework to enable sustainable EOL product management based on enriched information. We also propose a generic roadmap for model and methodology selection to assist practitioners in making smart decisions. n WC33 North Bldg 222C Transportation-Operations Contributed Session Chair: Yanshuo Sun, Florida State University, 2005 Levy Ave, Rm. 241 MRB, Tallahassee, FL, 32310, United States 1 - Mothership and Drone Routing Problem with Obstacles Stefan Poikonen, Assistant Professor, University of Colorado Denver, 1475 Lawrence Street, Denver, CO, 80202, United States, Bruce L. Golden The Mothership and Drone Routing Problem with Obstacles extends previous work on the mothership and drone routing problem, which considers a tandem between a ship and a drone. The drone is required to visit each of a set of targets. However, the drone has finite battery life and, thus, must coordinate with the ship. In previous work, we utilized second order cone programming as an embedded procedure. However, the addition of obstacles (dry land, political boundaries, etc.) which the mothership is not allowed to penetrate creates non- convexity in the problem. We propose a solution method which forms an initial solution than iteratively improves it using sequential second order cone programming. 2 - A Real-time Dynamic Model for Vehicle Routing Problem with Safety Criteria Qiong Hu, Auburn, Auburn, AL, 36832, United States, Alexander Vinel Driver’s safety is an important issue in the transportation, especially for long-haul truck industrial. We consider vehicle routing problem to enable safety constraint in decision making. We developed a dynamic model based on the statistical result of estimating risk under real-time driving conditions such as weather and traffic. Our model is based on real-life data collected by combining different sources. As a first step, value iteration and breath-first-search have been applied in our model to provide the best policy for a driver to schedule stop during route to minimize risk. 3 - Automatically Generating Shunting Operation Plan for District Local Train Based on Dynamic Programming Li Li, Southwest Jiaotong University, Chengdu, China, Gongyuan Lu, Bojian Zhang An LP model is proposed to describe the process of flat shunting operation and optimize the shunting operation plan for district local train, considering the initial and terminal status of cars on hand in the classification yard as the input variable. On the premise of ensuring the minimum number of coupling hooks, considering the use of shunting lines, the requirements of locomotive energy consumption, and the number of sliding hooks, to improve the marshaling efficiency and realize the operation plan’s auto-generation for the station sequence marshaling mode district local train.

n WC30 North Bldg 221C Warehousing Sponsored: TSL/Facility Logistics Sponsored Session Chair: Reem Khir, Georgia Institute of Technology, Atlanta, GA, United States 1 - An Integrated Cluster-based Storage Assignment Policy Yafeng YinB.M. De Koster, Erasmus University-Rotterdam, Planciusdreef 47, Bergschenhoek, 2661 RK, Netherlands, Masoud Mirzaei, Nima Zaerpour As ecommerce is growing, companies need more efficient warehouses. Amazon for example, allocates multiple correlated products on the same pod to reduce retrieval time. Turnover-based storage policies, only consider the frequency at which each product has been requested and ignore the frequency at which products are ordered jointly. To consider both information, we propose an integrated cluster allocation storage assignment model which minimizes the total retrieval time. Compared to full turnover-based policy, the proposed model can save up to 22%, in total retrieval time in an automated storage and retrieval system. However, it is data intensive and benefits depend largely on the order pattern. 2 - Dynamic Wireless Charging Lane Location Optimization in a Congested Warehouse Liu Su, University of South Florida, ENG 302, Tampa, FL, 33620, United States, Sung Hoon Chung, Kibaek Kim, Changhyun Kwon Forklifts with batteries are often used for material handing in a warehouse. With dynamic wireless charging, forklifts can be charged without work interruption. The optimal locations of dynamic wireless charging lanes are selected under the workflow congestion in a warehouse facility. Considering the uncertainty of demands, we formulate the wireless charging lane location problem as a two- stage stochastic programming model and propose a numerical method. 3 - Optimization of Sorting Center Operations in Express Parcel Delivery Network Reem Khir, Georgia Institute of Technology, Atlanta, GA, United States, Alan Erera, Alejandro Toriello We model a two-stage sorting process as a mixed-integer program to enable making decisions related to parcels’ routing and scheduling, and resource management and planning. The objective is to find a path for each parcel from the time it enters the sorting center to the time it leaves it such that each parcel finishes its sorting requirements no later than its cut-off time while the operational cost is minimized. Since finding optimal solutions of this problem is difficult for large-scale instances that are commonly found in practice, we investigate various ways to solve the problem using local search mechanisms. Chair: Xianghui (Richard) Peng, Eastern Washington University, 668 N. Riverpoint Blvd., Room 360, Spokane, WA, 99202-1677, United States 1 - Cross-training Policies in Repairable Spare Part Supply Systems Andrei Sleptchenko, Assistant Professor, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates, Hasan Turan In this talk, several results on the usage of Cross-Training Policies in Supply Systems for Repairable Spare Parts will be summarized. The presented results comprise simulation-based evolutionary heuristics for total cost optimization, as- well-as simple and scalable heuristics based on pooling of different parts into clusters by exploiting similarities of the repairable parts. The obtained results demonstrate that the optimal cross-training policies, or skill-server assignments, can help to improve the utilization of the repair servers and reduce the total system cost. 2 - Determining the Optimal Collection Policy for Returned Products in the Reverse Supply Chain A growing number of firms are facing the challenge of driving down costs in their reverse logistics network while maintaining a strategic competitive advantage through great customer service. This work focuses on the comparison of different collection policies that reduce the impact of product returns on a firm’s operational costs by leveraging economies of scale and optimizing the collection period across multiple initial collection points (ICPs) in a network before transshipping the returned products to a centralized return center (CRC). Moulik Kapadia, Northeastern University, Boston, MA, United States, Nizar Zaarour, Emanuel Melachrinoudis n WC32 North Bldg 222B Reverse Logistics & Supply Chains Contributed Session

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