Informs Annual Meeting 2017

WA36

INFORMS Houston – 2017

2 - Considering Crew Preferences in the Airline Crew Pairings to Improve the Crew Rostering Frederic Quesnel, GERAD, 9382 Joseph-Melancon, Montreal, QC, H2M 2H8, Canada, frederic.quesnel@gerad.ca, Francois Soumis, Guy Desaulniers The airline crew scheduling problem is usually divided in two steps : the crew pairing problem (CPP) and the crew rostering problems (CRP). While the goal of the CPP is to find feasible pairings at minimum cost, the CRP aims at finding a schedule that satisfy as many employee preferences as possible. The main challenge with this approach is that the pairings generated by the CPP may not be suitable for the objective of the CRP. In order to create pairings that are more compatible with the CRP, we propose a new mathematical formulation for the CPP that takes into account crew preferences. We show how such model can be solved with column generation and we present results showing the effectiveness of our method. 3 - Airline Reserve Planning Mingzhou Jin, University of Tennessee-Knoxville, 525D John D. Tickle Engineering Building, Industrial and Systems Engineering, Knoxville, TN, 37996, United States, jin@utk.edu, Ying Zhang, Suresh Rangan Reserve lines are planned in airlines for possible dropping of main crew lines. An approach integrating the demand forecasting, reserve pattern generation, reserve line optimization, and dynamic trip assignment is developed for improving the efficiency of reserve crew scheduling, measured by the utilization and coverage. A column generation algorithm is developed to generate patterns covering the forecasted reserve demands in a stochastic fashion. The approach can avoid the influence of forecasting errors caused by high uncertainty of reserve demands. 4 - An Improved Version of the Integral Simplex using Decomposition Algorithm Abdelouahab Zaghrouti, Kronos Canadian Systems Inc, 3535 Integral Simplex Using Decomposition (ISUD) is an iterative method that efficiently solves set partitioning problems for the transportation industry. We introduce a new version of ISUD that improves both quality and performance. With its new approach, given a good initial solution, it presents high chances of reaching the best solution without branching. Optimality is reached for large instances five times faster than the previous version. In addition to its performance, an important advantage of the new version is that it opens the possibilities of its extension to arbitrary binary problems. 351E Supply Chain Optimization Contributed Session Chair: Weihang Zhu, Lamar University, Beaumont, TX, United States, weihang.zhu@lamar.edu 1 - The Impact of Adopting 3D Printing Technology on Inventory and Pricing Decisions in a Two-echelon Supply Chain Sharareh Rajaei Dehkordi, PhD Student, New Jersey Institute of As 3D printing technology becomes agiler and better able to react customer demands, one important question for the retailers is whether they should provide 3D printing services in their brick-and-mortar store in addition to the traditional off-the-shelf product? If so, what should be the retailers pricing scheme and optimal inventory level to achieve ahigher profit? In this study, the retailers’ optimal joint decisions on inventory management policy and pricing scheme are developed while considering consumer preferences for self-designed, 3D printed products versus off-the-shelf products. 2 - A Supplier Selection and Supply Chain Coordination Model under Price Sensitive Demand and Profit Sharing Barbara Venegas Quintrileo, Pennsylvania State University, University Park, PA, 16801, United States, bbv105@psu.edu, Jose Antonio Ventura We study a supplier selection problem in a two stage centralized supply chain under price sensitive demand, formed by a buyer and a set of suppliers. Vendors have fixed production rates and produce a single item with no differences among them. A mixed integer nonlinear programming model under different lot sizing policies is presented, to determine the inventory policies and the final retail price for the customer, using a total supply chain optimization approach. Finally, a profit sharing method is proposed to allocate the benefits obtained through coordination. It restricts the model to pick solutions where each member’s rate of return (ROI) is at least a fixed portion of the supply chain’s ROI. Technology, 10 Hill Street, Apt 2N, Newark, NJ, 07102, United States, sr552@njit.edu, Wenbo (Selina) Cai Queen Mary Rd, Montreal, QC, H3V. 1H8, Canada, abdelouahab.zaghrouti@gerad.ca, Issmail El Hallaoui, Francois Soumis WA35

3 - Considering Production Planning and Scheduling Decisions in Supply Chain Network Design Gokhan Memisoglu, Applied Research Scientist, LLamasoft, LLamasoft, Inc., 201 South Division St. Suite 200, Ann Arbor, MI, 48104, United States, gokhan.memisoglu@llamasoft.com, Ali Taghavi, Nejat Karabakal, Jason D. Judd Production planning and scheduling decisions are important factors in supply chain design problems.. In this talk, we present how Supply Chain Guru (SCG), LLamasoft’s network optimization tool, incorporates these decisions into its generic network design formulation. 4 - Buyer and Supplier Strategies for Hedging against Risk in the Ethanol Industry? Iddrisu Awudu, Quinnipiac University, 12 Kaye Plaza, Apt E-22, Hamden, CT, 06514, United States, iddrisu.awudu@quinnipiac.edu, Anthony Afful-Dadzi e, Vinay Gonela We model an ethanol supply chain with price uncertainties. We incorporate the concept of copula. We develop a stylized linear optimization problem and solve the resulting problem using Multi-cut decomposition algorithm. We provide insights using a case study in North Dakota. 5 - An Order Acceptance Model for Hybrid Production Strategy The hybrid production strategy (HPS), a combination of the make-to-order (MTO) and make-to-stock (MTS), has been employed for over a decade. In order for hybrid-production based manufacturing to fully utilize available resources, a compatible order acceptance method is vital. This talk first presents a framework to explain what process the orders undergo until they are satisfied. Within the framework, an order acceptance model (OAM) is proposed. It is able to simultaneously consider production strategy, production capacity, and customer priority, and thus lead to higher profits. 351F Facilities Planning and Design Contributed Session Chair: Li Wei, Huazhong University of Science and Technology, Wuhan, China, liweianthea@gmail.com 1 - Overlap Packing Problem for Layout Design of Task Volumes in Spacecraft Churlzu Lim, Associate Professor, UNC-Charlotte, 9201 University City Boulevard, Charlotte, NC, 28223-0001, United States, clim2@uncc.edu, Simon M.Hsiang, Claudia Ramirez, Sherry S. Thaxton, Maijinn Chen, Jerry Myers This study considers a packing problem that searches for a minimum-volume cube container to pack a given number of variously sized cuboids while allowing overlap between cuboids to certain extent. The problem was developed as part of designing arrangements of task volumes performed by astronauts in a spacecraft for a prolonged period of time. Mixed-integer linear programming model is proposed to minimize the volume of the cube container while enforcing additional constraints such as overlap limits, adjacency requirements, and orientation options. Numerical examples will be discussed. 2 - Techniques for Improving Safety on Medium Voltage Electrical Equipment Raymundo Rivera, PhD Student, UT Health San Antonio, 1814 N Palmetto Ave., San Antonio, TX, 78208, United States, riverar5@uthscsa.edu Raymundo Rivera, PhD Student, Mississippi State University, MS, United States, riverar5@uthscsa.edu, Linkan Bian In the United States, the medium voltage electric grid and its complex electrical components which include customer-side automatic transfer switches, transformers, switchgear and breakers receive minimal inspections. When electrical failures develop the most critical issues are often the only ones addressed while the lesser problems are left untouched and fester until the next electrical failure occurs. This paper introduces the classification of datasets based on ultrasound waveforms, age, and type of equipment in order to minimize arc flash hazards to electrical personnel, minimize power outages, minimize lost revenue and reduce the risk of lost customer data. Weihang Zhu, Associate Professor, Lamar University, PO Box 10032, Beaumont, TX, 77710, United States, weihang.zhu@lamar.edu, Arash Abedi WA36

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