Informs Annual Meeting 2017

TD35

INFORMS Houston – 2017

TD36

4 - Quantile Regression Based Estimation of Statistical Contingency Fuel Mark M. Hansen, University of California-Berkeley, 114 McLaughlin Hall, Berkeley, CA, 94720, United States, mhansen@ce.berkeley.edu We use quantile regression to estimate statistical contingency fuel based on the specific circumstances of a given flight, and the fuel savings that could result from using this approach compared to current practice. 351E Supply Chain Optimization Contributed Session Chair: Vinay Gonela, Texas A & M University, Killeen, TX, United States, vinay.gonela@tamuct.edu 1 - Mixed-fleet Sizing and Routing with Electric Vehicles for Maximum Profit Isil Koyuncu, Teaching and Research Assistant, The University of This talk presents a maximum profit mixed-fleet electric VRP with traditional and electric vehicles. A set of customers are willing to pay an EV premium to reduce their supply chain carbon footprint. We investigate the exact solution of the problem via Branch and Price Algorithm and compare with heuristic algorithms. 2 - Potential Revenue of Wasted Plastic Bottle Auction in Japan Kazuaki Okubo, Associate Professor, Ehime University, 3 Bunkyo machi, Matsuyama city, Matsuyama, 790-8577, Japan, okubo@cee.ehime-u.ac.jp This study explores the potential revenue of municipalities, who collect and sell waste plastic bottles to recycling firms on auctions. I use the auction data in Japan to estimate potential bids and formulated a mixed integer programming model to derive the optimal combination of municipalities and recycling firms that maximizes municipalities’ revenue. I found that the revenue in the optimal combination is larger than in the observed combination, especially in Kanto region where there are relatively many recycling firms. The distances between municipalities and recycling firms become smaller in the optimal combination to reduce transportation cost. 3 - Carbon Emission Reduction Strategies for Two Competing Firms under Cap and Trade Regulation with Consumers Preference Tao Li, Santa Clara University, 2730 Park Ave, Apt 3, Santa Clara, CA, 95050, United States, tli1@scu.edu This paper develops price and low-carbon competition models between one socially responsible manufacturer and one regular manufacturer under the influences of consumers’ low-carbon preference. We assume that the responsible manufacturer is a pioneer in low-carbon market. Our research questions address how the regular manufacturer’s low-carbon production choice is affected by factors such as cap-and-trade policy and competitive environment. 4 - Improving Environmental Sustainability within Emission Control Areas in Liner Shipping: Review and Analysis of Different Regulations Maxim A. Dulebenets, Florida A&M.University-Florida State University, 2300 Bluff Oak Way, Apt. 8408, Tallahassee, FL, 32311, United States, mdlbnets@gmail.com, Ren Moses, Eren Erman Ozguven, Thobias Sando Emissions produced by oceangoing vessels negatively affect the environment and living organisms. Several regulations were released by the International Maritime Organization (IMO) to alleviate negative externalities from maritime transportation. Certain polluted areas were designated as “Emission Control Areas”. This study aims to perform a comprehensive review of the existing IMO regulations and conduct the assessment of advantages and disadvantages from introducing restrictions on the emissions produced within “Emission Control Areas”. 5 - Designing a Sustainable Biomass Based Electricity Supply Chain Vinay Gonela, Assistant Professor, Texas A.& M.University, FH 218K, 1001 Killeen Place, Killeen, TX, 76549, United States, vinay.gonela@tamuct.edu, Iddrisu Awudu This paper focuses on designing a sustainable biomass based electricity supply chain (BESC) under uncertainties. All the three economic, environmental and social aspects of sustainability are considered. A Multi-objective stochastic mixed integer linear programming model is developed that aims to design optimal BESC under carbon tax and unemployment rate considerations. The result provides strategic BESC decisions. In addition, sensitivity is conducted to determine the impact of various factors on the BESC design. TD35 Alabama, Alston Hall Box 870226, Tuscaloosa, AL, 35487, United States, ikoyuncu@crimson.ua.edu, Mesut Yavuz

351F Project Management Contributed Session

Chair: Homayoun Khamooshi, George Washington University, 2201 G Street NW, Funger 415, Washington, DC, 20052, United States, hkh@gwu.edu 1 - Multi-mode Resource-constrained Project Scheduling with Uncertain Activity Cost Fang Xie, Shandong Technology and Business University, Shandong Province Yantai I City Laishan District #191, Yantai, 264005, China, xiefangmm@163.com, Haitao Li, Zhe Xu In this paper, we study the multi-mode resource-constrained project scheduling problem under uncertain activity cost. A nonlinear integer programming model with the minimum risk of project cost overrun is formulated. To overcome the computational challenge of solving large instances, several heuristic algorithms are proposed and implemented to obtain quality solutions in reasonable computational time. Through extensive computational experiments, the effectiveness of our algorithms are demonstrated. Furthermore, related conclusions are also discussed. 2 - Reactive Scheduling Procedures for Project Resource Leveling with Uncertain Activity Durations Hongbo Li, Assistant Professor, Shanghai University, Baoshan District, Shangda Road 99, Shanghai University, Shanghai, 200444, China, ishongboli@gmail.com Recent research in the area of project resource leveling has paid attention to robust resource leveling, which aims at obtaining a robust baseline schedule by considering both resource leveling and activity start time stability. However, such a schedule may still not fully protect a project from disruptions in uncertain environments. Therefore, we study reactive scheduling procedures for resource leveling. We try to repair a disrupted schedule, such that the recovered schedule deviates as little as possible from the original one while maintaining a leveled resource usage. Extensive computational experiments on benchmark instances are conducted to evaluate the proposed procedures. 3 - The Integration of Resource Allocation and Time Buffering for Bi-objective Robust Project Scheduling Yangyang Liang, Huazhong University of Science and Technology, Wuhan, Hubei , P.R. China, China, yangliang0419@sina.com, Nanfang Cui In this paper, we aim at constructing a proactive schedule that is not only short in time but also less vulnerable to disruptions. Firstly, a bi-objective scheduling model is proposed in the presence of activity duration variability. Then a two- stage algorithm is developed which deals with a robust resource allocation problem in the first stage and optimally determines the position and the size of time buffers using a simulated annealing algorithm in the second stage. Finally, an extensive computational experiment demonstrates the superiority of the combination between resource allocation and time buffering. 4 - Solution Approaches for a Project Scheduling Problem with Multiple Modes and a Single Nonrenewable Resource Cansu Altintas, Research Assistant, Middle East Technical University, Odtu Kampusu Endustri Muhendisligi, Oda136, Ankara, 06800, Turkey, cansubulutaltintas@gmail.com, Meral Azizoglu We study a project scheduling problem with multiple activity modes where mode is defined by an activity duration and resource consumption amount. We assume that there is a single nonrenewable resource and it is released in scheduled times at specified quantities. Our problem is to select the modes and activity timings to minimize the project makespan. We give an efficient mathematical formulation and propose an alternative combinatorial solution approach. We discuss and compare the efficiencies of both methods, mathematical formulation and combinatorial algorithm. 5 - Managing Service Systems via Disguised Queues Eren Basar Cil, University of Oregon, Lindquist College of Business, Eugene, OR, 97403-1208, United States, erencil@uoregon.edu Touristic attractions, such as observatory decks, boat tours, museums, have recently started to manage their operations via disguising parts of their waiting lines. If customers are not aware of the hidden queues, the firm can easily boost its revenues by engaging in queue disguising behavior. Our goal in this paper is to investigate the impacts of strategic customer behavior on the firm’s queue disguising decisions and profits. We show that the firms can significantly benefit from disguised queues if customers act strategically, especially when the queue disguising is harmful under non-strategic customers.

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