Date	Speaker	Title and Abstract
Friday, Aug. 5th *3:00 p.m.* *SUR 2750*	Jingxin Guo Simon Fraser University	Optimal Locations of On-line and Off-line Rework Stations in a Serial Production System Abstract: The production rate and product quality are two vital concerns for any manufacturing industry. Number of defective items reduces production rate and increases unit production cost. Moreover, if nonconforming items reach to the customers then manufacturer’s goodwill may drastically go down. Thus, quality inspection is treated as an inherent part of manufacturing. In this research, an N-stage serial production line with an inspection station at the end of it is considered to make decisions concerning this issue. On detecting a defective item at the end of the line it is scrapped or repaired at regular workstation or is sent to an off-line rework station for repair. Assuming each workstation produces a single type of defect a unit cost function is developed for alternative decisions on each type of defect. In order to minimise the unit cost of production and determine an appropriate decision for individual defect types, a fractional mixed integer nonlinear programming is formulated. After transformation to a mixed integer linear programming problem it is solved optimally. A small problem from garments industry is described in detail to show the solution procedure with a branch and bound method. Empirical tests with up to 40 workstations are permed to show the efficiency of the solution process. (The talk will discuss the paper: Md. Shahriar J. Hossain & B. R. Sarker (2016) Optimal locations of on-line and off-line rework stations in a serial production system, International Journal of Production Research, 54:12, 3603-3621)
July 28th *SUR 5380*	Hubert Pun Ivey School of Business University of Western Ontario	Creating Competitors: When Advertising Encourages Copycats Abstract: We use a two-period game theoretical model to examine the decisions of a manufacturer and a copycat firm. Specifically, the manufacturer's product has a higher quality than that of the copycat product. The manufacturer decides on the amount of its market expansion advertising investment in the first period and on its pricing strategy in both periods; the advertising investment increases the "size of the pie," but eventually, the manufacturer may end up inadvertently sharing the benefits with the copycat. After the first period, the copycat makes a market-entry decision, and, if it opts to enter, it also decides on a pricing strategy. The customers are forward-looking strategic, and they decide whether or not to buy, when to buy, and which product to buy. We find that, interestingly, lower quality levels of the manufacturer's product may increase the manufacturer's prices and profit. Moreover, the manufacturer may be worse off when customers are more likely to purchase its product immediately rather than wait for a price reduction or for the copycat's product. Finally, the copycat may be worse off when customers may withhold their purchases in the first period in anticipation of the possibility of copycat product becoming available in a later period.
July 21st *SUR 2750*	Rimi Sharma Simon Fraser University	Discrete Optimization Models in Portfolio Management Abstract: Portfolio optimization collectively as a term is a mathematical approach to making investment decisions amid a group of financial instruments or assets. This concept has been helpful in the development and understanding of financial markets and financial decision-making. In this talk we present a survey of some important MILP based approaches for solving portfolio management problems, the real features that has been incorporated in the model and the solution methodologies to the resulting models.
Friday, June 24th *10:00 a.m.* *SUR 3040*	Yash Aneja Odette School of Business University of Windsor	Survivable Regenerator Location Problem Abstract: We consider the problem of locating regenerators optimally on certain nodes in an optical network to ensure that all nodes can communicate with each other even when (at most) one edge (optical fiber), of the physical network topology, fails. The quality of an optical signal propagating through a wavelength division multiple multiplexed (WDM) network deteriorates due to physical layer impairments such as optical noise, chromatic and polarization mode dispersion, cross-phase modulation and cross talk. When the quality of signal becomes unacceptable, it is necessary to carry out the 3R-generation (re-amplify, reshape and re-time) on the optical signal to bring the signal to its original quality. The optical reach is defined as the maximal distance a signal can travel before it requires the regeneration. This NP-hard problem can be formulated as a set-covering problem with an exponential number of constraints which are known only implicitly. We study the polyhedral structure and a branch-and-cut algorithm for this problem. We also consider several greedy approaches to obtaining good solutions to this problem. We show that a special case results in an approximation algorithm with a performance ratio of “ln(delta)”, the natural logarithm of delta, where delta is the maximum degree of a given graph.
Thursday, Apr. 7th *11:30* *SUR 3290*	J. Hung, B. Lo and F. Si Simon Fraser University	Math 402W Operations Research Clinic project presentation Improving Public Transit Fare System: A Case Study for TransLink Fare System in Metro Vancouver
Thursday, Apr. 7th *10:30* *SUR 3290*	O. Jackson and I. Martinez Simon Fraser University	Math 402W Operations Research Clinic project presentation A Queueing Network Model for Refugee Language Courses in Vancouver
Wednesday, Apr. 6th *6:00 pm* *SUR 5360*	Craig Mathews, Fraser Health Authority and Ali Saremi, Provincial Health Services Authority	Canadian Operational Research Society Seminars and Networking Event Craig Mathews and Ali Saremi will discuss projects they have been involved in at Fraser Health.
Friday, Apr. 1st *3:30 p.m.* *SUR 3040*	Timothy Chan Mechanical and Industrial Engineering University of Toronto	Goodness of Fit in Inverse Optimization Abstract: The classical inverse optimization methodology for linear optimization assumes a given solution is a candidate to be optimal. Real data, however, is imperfect and noisy: there is no guarantee that a given solution is optimal for any cost vector. Inspired by regression, this paper presents a unified framework for cost function estimation in linear optimization consisting of a general inverse optimization model and a corresponding goodness-of-fit metric. Although our inverse optimization model is in general nonconvex, we derive a closed-form solution and present the corresponding geometric intuition. Our goodness-of-fit metric, rho, termed the coefficient of complementarity, has similar properties to R2 from regression and is quasiconvex in the input data, leading to an intuitive geometric interpretation. We derive a lower bound for rho that possesses the same properties but is more tractable. We demonstrate the application of our framework for model estimation and evaluation in production planning and cancer therapy.
Mar. 10th via COCANA (Kelowna)	Sedi Bartz UBC Okanagan	New Dominant Properties of the Proximal and the Resolvent Averages Further details available from the COCANA Website.
Mar. 3rd via COCANA (Kelowna)	Sébastien Le Digabel Polytechnique Montréal	Black-Box Optimization: Algorithms and Applications Further details available from the COCANA Website.
Feb. 11th via COCANA (Kelowna)	Young-Heon Kim UBC	Optimal Martingale Transport in General Dimensions Further details available from the COCANA Website.
Feb. 4th via COCANA (Kelowna)	Pontus Giselsson Lunds Universitet (Sweden)	Tight Linear Convergence Rate Bounds for Douglas-Rachford Splitting Further details available from the COCANA Website.
Nov. 26th	Binay Bhattacharya Simon Fraser University	Facility Locations in Dynamic Networks Abstract: This talk discusses the problem of locating facilities in dynamic networks. In dynamic flow models it takes time for the flow to pass an arc, the flow can be delayed at nodes. An edge’s capacity represents the amount of items that can enter the edge in a unit time. Dynamic flow problems require moving a set of items from source nodes to sink nodes in minimal time. Congestion occurs at a vertex when more items start waiting at the vertex to enter an edge than can immediately leave the vertex. Finding a quickest dynamic flow usually requires designing flows that avoid (too much) congestion. These problems have been motivated by the problem of evacuation planning during natural disasters such as earthquakes, weather disturbances. Each vertex of a dynamic flow network represents a source with a certain number of people. The objective of the planning is to determine an evacuation schedule to move everybody from all the source nodes to evacuation centers (sinks) using minimal time. The evacuation problem can be viewed as a generalization of classical k-center and k-median problems. This talk discusses some recent work on graph evacuation problem carried out at SFU. It is a joint work with Tiko Kameda, Ante Custic, Yuya Higashikawa and Naoki Katoh.
Nov. 12th via COCANA (Kelowna)	Fang Fang and Ma Hui UBC Okanagan	Energy-Efficient Resource Scheduling for Non-Orthogonal Multiple Access (NOMA) Wireless Network: A DC Programming Approach (Fang) and Convex Analysis Based Beamforming of Decode-and-Forward Cooperation for Improving Wireless Physical Layer Security (Hui) Further details available from the COCANA Website.
Oct. 15th via COCANA (Kelowna)	Warren Hare UBC Okanagan	Proximal Bundle Methods for Inexact Oracle Functions Further details available from the COCANA Website.
Oct. 10th *8:30-4:30*	WCOM Hosted by UBC Okanagan	Details of the Fall 2015 West Coast Optimization Meeting here.
Oct. 1st via COCANA (Kelowna)	Shawn Xianfu Wang UBC Okanagan	Strongly convex functions, Moreau envelopes, and the generic nature of convex functions with strong minima Further details available from the COCANA Website.
Tuesday, Sept. 22nd Joint O.R. and Discrete Math Seminar *Burnaby* *1:30* *AQ K9509*	Ilya Shmulevich Institute for Systems Biology	Probabilistic Boolean Networks as Models of Genetic Regulatory Networks Abstract: I will present Probabilistic Boolean Networks (PBNs), which are models of genetic regulatory networks that i) incorporate rule-based dependencies between genes; ii) allow the systematic study of global system dynamics; iii) are able to cope with uncertainty; iv) permit the quantification of the relative influence and sensitivity of genes in their interactions with other genes. PBNs share the appealing rule-based properties of Boolean networks, but are robust in the face of uncertainty. The dynamics of PBNs can be studied in the context of Markov Chains, with standard Boolean networks being special cases. I will also discuss the relationship between PBNs and Bayesian networks - a family of graphical models that explicitly represent probabilistic relationships between the variables. A major objective is the development of computational tools for the identification of potential targets for therapeutic intervention in diseases such as cancer. I will describe several approaches for finding the best genes with which to intervene in order to elicit desirable network behavior.
Sept. 17th	Tamon Stephen Simon Fraser University	Covering Grid Points with Rectilinear Subspaces Abstract: We consider a problem of covering a box of grid points with axis-aligned affine subspaces. The objective is to do this so that each co-ordinate hyperplane containing grid points contains a subspace from the cover, and to minimize the number of elements in the cover. We find the minimum size of such a cover, and characterize the covers attaining this minimum. This problem arises in connection with the colourful simplicial depth problem: a (mod 2) version of this result would prove the colourful simplicial depth conjecture as a corollary. In fact, an example shows that the the (mod 2) generalization does not hold. However we conjecture that it almost holds in some relevant respects.