2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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4 - Robust Allocation Of Testing Resources In Reliability Growth
MohammadHossein Heydari, University of Arkansas, Fayetteville,
AR, United States, , Kelly Sullivan
Reliability growth testing seeks to improve system reliability by identifying and
removing failure modes. Recent models maximize system reliability by allocating
limited testing resources across the system’s components, each of which exhibits
reliability growth according to the AMSAA model (Crow, 1974) with known
parameters. We extend this research to solve a robust version of this problem in
which AMSAA parameters are uncertain but assumed to lie within a budget-
restricted uncertainty set.
MD70
Acoustic- Omni
Transportation, Rail I
Contributed Session
Chair: Ginger Yi Ke, Memorial University of Newfoundland, Faculty of
Business Administration, Memorial University of Newfoundland, St.
John’s, NL, A1B 3X5, Canada,
1 - Passenger Centric Railway Planning
Yousef Maknoon, EPFL, Lausanne, Switzerland,
, Tomas Robenek, Stefan Binder,
Michel Bierlaire
Traditional railway systems use operations research techniques to optimize their
system. Most of the time such mathematical models take only operators’ cost and
benefit into account. However, passengers’ decision as the main users of such
systems play an important role in the performance of such networks. We
introduce a state of the art methodology that takes both sides (demand and
supply) into account in timetable design as well as recovery plans for trains.
2 - The Locomotive Planning Problem With Alternative Train Speeds
An Integrative Environmental Perspective
Ginger Yi Ke, Memorial University of Newfoundland, Faculty of
Business Administration, Memorial University of Newfoundland,
St. John’s, NL, A1B 3X5, Canada, , Kan Fang,
Manish Verma
We develop multi-objective models for the locomotive planning problem to
minimize the GHG emissions and the operational costs. The amount of GHG
emitted by a locomotive depends on the train speed, train load, and the
locomotive type, etc. We determine the assignment of locomotives to each train,
so that sufficient power can be provided to pull the trains; we generate train
schedules that meet customer demands within different time windows, and
determine the number of active, deadheading, light traveling locomotives, and
the train-to-train connections (e.g. consist busting) for each train. Real-life
railway systems are used for numerical experiments to provide additional
managerial insights.
MD71
Electric- Omni
Vehicle Routing I
Contributed Session
Chair: Michael F Gorman, Professor, University of Dayton, 300 College
Park, Dayton, OH, 45469, United States,
1 - An Optimization Method Of Petrol Distribution Considering
Drivers’ Workload Balance
Lijun Sun, Associate Professor, Dalian University of Technology,
2 Linggong Road, Ganjingzi District, Dalian City, 116023, China,
Haiyang Shi
We present a multi-objective optimization model of petrol distribution
considering drivers’ workload balance based on Adams’s equity theory. A
heuristic algorithm is designed based on the NSGA-II algorithm. Computational
results show that the proposed algorithm can generate a non-dominated solution
set corresponding to distribution plans that perform well both in the total
distribution cost and drivers’ workload balance.
2 - Two Level Logic-based Benders Decomposition For Optimal
Service NetworkDesign
Amin Hosseininasab, Carnegie Mellon University, Pittsburgh, PA,
United States, , Fatma Gzara
We present a new continuous time network and model for the service network
design problem (SNDP). SNDP addresses the planning of operations for freight
transportation carriers. Given a set of requests to transport commodities from
specific origins to specific destinations with given availability and delivery times,
SNDP determines a continuous movement of vehicles. We propose a two-stage
Logic-based Benders decomposition and develop several valid cuts for SNDP.
Numerical results show the benefits of the continuous time approach and the
effectiveness of the solution methodology.
3 - A Multi Stage Heuristic Solution For A Consultant Assignment And
Routing Problem
Andrew Junfang Yu, Associate Professor, The University of
Tennessee - Knoxville, 411 B. H. Goethert Pkwy., MS 19,
Tullahoma, TN, 37388-9700, United States, ,
Brett Shields
In this study, a heuristic algorithm is developed for a novel Vehicle Routing
Problem (VRP), namely the Heterogeneous Fleet Vehicle Routing Problem with
Multiple Depots, Fixed Visits, and Priority Matching. The heuristic is four stage, in
which the first stage is a conversion of skills and priorities to one set, second a
listing of consultants is constructed based on the items in step one, third a fixed
visit based assignment is given considering the availability of consultants and
clustered demand, and lastly an optimal routing for each consultant is
determined.
4 - Two Echelon Location Routing Problem In The Presence Of
Third Party Logistics
Khosro Pichka, PhD Student, S. B. Lubar School of Business, 3202
N. Maryland Ave., Milwaukee, WI, 53211, United States,
, Amirsaman Hamzeh Bajgiran, Xiaohang Yue,
Jaejin Jang, Matthew Petering
This paper addresses a two echelon location routing problem (2E-LRP)
considering third party logistics. A 2E-LRP is a variant of the classical LRP;
however, it seeks to find a set of vehicle routs in two echelons. First, from a single
depot to a set of possible satelites and second, from the opened satelites to
customers. In spite of the large amount of research on LRPs, the 2E-LRP has
received very little attention from researchers. A mixed integer program (MIP)
formulation is proposed, and a hybrid heuristic algorithm is developed to solve its
medium and large size problems.
5 - Inventory-based Delivery Scheduling And Routing
Michael F Gorman, Professor, University of Dayton,
300 College Park, Dayton, OH, 45469, United States,
Milk-run deliveries of product to customers depend on both inventory levels and
customer proximity to one another. We describe a system designed to improve
delivery economies through careful assessment of the trade-offs between stopping
costs and mileage costs. We use k-means clustering to great groups of “like”
customer in both geography and inventory depletion dates. We use a novel
“furtherst neighbor” heuristic to then sequence deliveries. We discuss the
application of this approach at a US manufacturer.
MD72
Bass- Omni
Supply Chain Mgt VIII
Contributed Session
Chair: Nathalia Hernandez, Universidad del Norte, Km 5 Vía Puerto
Colombia, Barranquilla, AA1569, Colombia,
1 - An Econometric Analysis Of Omnichannel Retailing Using
Data Analytics
Serkan M. Akturk, Texas A&M University, 4217 TAMU,
Wehner 320 M, College Station, TX, 77843-4217, United States,
, Michael Ketzenberg
The advent of omnichannel technologies, like ship-to-store capability, enable
integration of both physical and electronic marketplaces and thereby offer
consumers shopping flexibility and enhanced services. For a retailer, these
capabilities require significant investment in order to deliver a seemless shopping
experience, yet hold the promise of greater customer loyalty, higher marketshare,
and increased competitiveness. We assess this promise by analyzing the impact of
ship-to-store capability on a retailer’s performance using transactional data from a
national retailer.
2 - Determining The Optimal Level Of Supply Chain Forecast
Coordination With Bidirectional Option Contracts
Seong-Hyun Nam, Professor, University of North Dakota,
2517 Sand Hills Avenue, Grand Forks, ND, 58201, United States,
We have studied bidirectional option contracts associated to demand uncertainty.
By analyzing how the buyer’s procurement and supplier’s production decisions
are affected by the level of the coordination/collaboration of demand forecast
under bidirectional option contracts, we have found that the optimal procurement
for buyer and optimal production strategy for supplier to maximize supply chain
surplus is associated with the level of forecast collaboration under bidirectional
option contracts.
MD72