2016 INFORMS Annual Meeting Program

WA27

INFORMS Nashville – 2016

WA26 110B-MCC Display Advertising Markets

4 - Planning Models For Skills-sensitive Surgical Nurse Staffing Maya Bam, University of Michigan, Ann Arbor, MI, United States, mbam@umich.edu, Maya Bam, University of Michigan Health System, Ann Arbor, MI, United States, mbam@umich.edu, Zheng Zhang, Brian T Denton, Mark P Van Oyen, Mary Duck, Joshua Pigula Surgical nurses are essential resources in the surgery delivery system. However, surgical nurse staffing decisions present a challenge due to the stochastic nature of surgical demand, nurse availability, skill requirements, and hospital regulations. Based on collaboration with a large academic hospital, we present planning level optimization models to group services into teams based on difficulty and overnight call volume, and then assign shifts to services and teams subject to skill requirements. We present results that provide insight into optimal nurse staffing decisions based on a large hospital data set. WA25 110A-MCC Logistics I Contributed Session Chair: Jiahong Zhao, Guangdong University of Technology, No.100 Waihuanxilu Daxuecheg, Guangzhou, 510006, China, zhaojiahong1@126.com 1 - The Regional Logistics Hubs Location Problem Based On The Topsis And Genetic Algorithm The Case Of Sichuan In China Si Chen, Dr., Southwest Jiaotong University, #111 The First Block of North Erhuan Road, Chengdu, 610031, China, chensi@swjtu.edu.cn, Dong Chen, Mi Gan The regional logistics demands, which are the key factor for logistics hubs location problem, are changing with the developing regional economic and the structure of industry. Noted that different industries will result in different kind of logistics demand, we aims to modeling the regional logistics hubs location problem with consider of industries affected logistics demand. Then the real data case of Sichuan province is employed to verify the feasibility of proposed models and approach, the results indicate that Chengdu, Leshan and Deyang is selected from 18 candidate cities as the comprehensive logistics hub, cross-regional logistics hub and internal-oriented logistics hub, respectively. 2 - Data Driven Approach To Crowd Delivery In Last Mile Loo Hay Lee, National University of Singapore, 10 Kent Ridge Cresent, Industrial and Systems Engineering, Singapore, 119260, Singapore, iseleelh@nus.edu.sg, Yuan Wang, Dong Xiang Zhang, Ek Peng Chew In urban logistics, the last-mile delivery has become more challenging with the continuous growth of E-commerce. In this paper, we propose an effective large- scale mobile crowd-tasking model in which a large pool of citizen workers are used to perform the last-mile delivery. To efficiently solve the model, we present network min-cost flow based method with pruning techniques and constrained clustering approach to partition large data points. Comprehensive experiments were conducted with Singapore and Beijing datasets. The results show that our solution can support real-time delivery optimization in the large-scale mobile crowd-sourcing problem. 3 - Adaptive Warehouses: Look At The Past, Not The Future Nima Zaerpour, Assistant Professor of Operations Management, California State University San Marcos, 333 S Twin Oaks Valley Rd., Markstein 446, San Marcos, CA, 92096, United States, nzaerpour@csusm.edu, Sholeh Norouzzadeh The growth of online shopping is bringing new challenges to warehouses. For instance, Amazon receive 35 orders/second, each including few items. The timing for delivery varies between the same day deliveries to a couple of days. The product popularity and assortment varies frequently influenced by various factors. Thus, warehouses need to become more responsive to customers and more adaptive to changes while the customer information does not become available sufficiently in advance. We ask the following: can self-learning techniques improve efficiency of warehouses and reduce the time/effort required to retrieve a product for a customer order? This paper tries to answer this question. 4 - A Location Inventory Routing Optimization Model For Explosive Waste Management Jiahong Zhao, Guangdong University of Technology, No.100 Waihuanxilu Daxuecheg, Guangzhou, 510006, China, zhaojiahong1@126.com, Ginger Yi Ke Recently, attentions have been drawn to reducing the risks derived from facility location, inventory management, and multi-depot vehicle-routing of the explosive waste management. In this research, risks are assessed as impact solids with certain hazardous radii posed by explosions happening en route and at site. An optimization model minimizing the total cost and risk is developed to determine the corresponding location-inventory-routing plan. In addition to a well-defined solution procedure, a real-world problem of Southwest China is examined to provide further managerial insights.

Invited: Auctions Invited Session

Chair: De Liu, Carlson School of Management, 3-163 CSOM, University of Minnesota, Minneapolis, MN, 55455, United States, deliu@umn.edu Co-Chair: Dengpan Liu, Iowa State University, 3321 Gerdin Building, Ames, IA, 50011, United States, dliu@iastate.edu 1 - Closed-loop Versus Open-loop Advertising Competition In Electronic Retailing: Operational And Organizational Considerations Dengpan Liu, Iowa State University, dliu@iastate.edu This study examines two different types of dynamic advertising competition, namely, closed-loop and open-loop, among e-retailing firms. In particular, we focus on how the considerations of IT operations and organizational structure would affect firms’ performance in dynamic advertising competitions. Using a differential game framework, we find that firms can be better off engaging in the closed-loop competition. Another interesting finding is that the advantage of flexibility in closed-loop game may reduce as IT becomes more costly. 2 - Architecture Of In App Ad Recommender System Anik Mukherjee, Indian Institute of Technology - Madras, India, anikit.jgec@gmail.com Increased adoption of smartphones has caused mobile advertising to be the second-most revenue-generating medium among all forms of existing online advertising. Appl developers try to monetize their apps by selling in-app ad-spaces to the advertisers through various intermediaries such as ad-networks. Surveys indicate that mobile ad campaigns are not as successful as they can be due to inappropriate audience targeting and user-apathy toward such ads. This motivates the need for a system, where both the parties gain from the in-app advertising eco-system. So, we propose an architecture of design-science artifacts for an ad- network, to meet the objectives of both these stakeholders. 3 - Procurement Policies For Mobile-promotion Platforms Manmohan Aseri, University of Texas - Dallas, Richardson, TX, 75080, United States, mxa113030@utdallas.edu Mobile-Promotion platforms such as Cidewalk enable advertisers to directly launch their personalized mobile advertising campaigns. These platforms contract with advertisers to provide a certain number of impressions on mobile apps in their desired sets of geographic locations within their desired time durations; the execution of each such contract is referred to as a campaign. In practice, campaigns arrive dynamically over time and the platform bids in real-time at an ad exchange to fulfill their demands. Our analysis offers a rolling-horizon procedure in which the platform periodically recomputes its procurement/bidding policy and its policy for allocating the impressions to the campaigns.

WA27 201A-MCC

Humanitarian Operations Management Sponsored: Manufacturing & Service Oper Mgmt Sponsored Session

Chair: Alfonso J Pedraza-Martinez, Indiana University, 1309 E 10th Street, Bloomington, IN, 47405, United States, alpedraz@indiana.edu 1 - Volunteer Management In Charity Storehouses Alfonso J Pedraza-Martinez, Indiana University, Kelley School of Business, 1309 East 10th Street, Bloomington, IN, 47405, United States, alpedraz@indiana.edu, Maria Besiou We study volunteer management at a large faith-based organization. The whole supply chain operates exclusively with volunteers (from supply to delivery). We focus our study on the preparation of beneficiaries’ orders by volunteers in a storehouse. There are different categories of volunteers; some are more experienced while others may work in the system for the first time. The volunteers’ arrival in the system and their skills are uncertain. Using empirical data we explore the drivers of on-time order fulfillment at the storehouse level.

371