Reference number : GC-2017-Q1-03325, amendment number : , agreement type : G, recipient legal name : Berman, Oded (University of Toronto), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : This proposal is a continuation of my former proposal funded by NSERC. As will be shown in the proposal I have made considerable progress over the last 5 years. 
Early location models assumed that facilities can serve all customers without delay, that they never fail and that decisions on inventory and marketing can be made separately. Four major areas of combined location models that relax these assumptions are proposed. 
 Reliability-Location Models: This research seeks to gain a better understanding of how disruptions affect optimal location decisions. I suggest 6 directions to achieve it. Since in most applications, customers&rsquo; demand is distributed continuously while most research assumes discrete demand, a main focus of the proposed research is on location problems with continuous demand. The work will assist managers in making better decisions on budget allocation, on constructing new facilities, on improving reliability of existing facilities and on improving the information system. 
 Marketing-Location Models: Our proposed research belongs to the intersection of facility location models and marketing diffusion models. The earlier research typically ignores the marketing support that the product receives and the temporal effects like word-of-mouth while the latter tends to ignore where the product should be available and the effect of travel distances on the demand. The main goal is to understand better the dynamics of the system and to develop new models and extend existing ones in order to show the implications of combining marketing diffusion models and location decisions. I suggest 4 directions of research. 
 Queuing-Location Models: In the class of models we focus on, customers generate a stochastic stream of demands, servers have limited capacity, service times are stochastic and therefore customers arriving at the facilities must wait sometimes or leave the facility. The goal is to design a system where the main decisions are: number of facilities, their locations, their service capacities and the assignment of customers to facilities. I suggest 7 directions of research that aim at helping service managers improve system quality. 
 Inventory-Location Models: Traditionally optimal management of supply chain problems and location problems were studied separately. As this usually may lead to inefficiencies and high costs, we plan to consider them jointly. The main decisions include finding the number of facilities (suppliers, retailers and distribution centers (DCs)), their locations and the amount of inventory to order. I propose 5 directions of research that aim at gaining a better understanding of joint inventory and location decisions. We also anticipate contribution to the methodologies of both areas separately. 
We note that some of the issues considered in this proposal such as reducing waiting times (e.g., in healthcare) and locating reliable facilities are important in Canada., program purpose french : This proposal is a continuation of my former proposal funded by NSERC. As will be shown in the proposal I have made considerable progress over the last 5 years. 
Early location models assumed that facilities can serve all customers without delay, that they never fail and that decisions on inventory and marketing can be made separately. Four major areas of combined location models that relax these assumptions are proposed. 
 Reliability-Location Models: This research seeks to gain a better understanding of how disruptions affect optimal location decisions. I suggest 6 directions to achieve it. Since in most applications, customers&rsquo; demand is distributed continuously while most research assumes discrete demand, a main focus of the proposed research is on location problems with continuous demand. The work will assist managers in making better decisions on budget allocation, on constructing new facilities, on improving reliability of existing facilities and on improving the information system. 
 Marketing-Location Models: Our proposed research belongs to the intersection of facility location models and marketing diffusion models. The earlier research typically ignores the marketing support that the product receives and the temporal effects like word-of-mouth while the latter tends to ignore where the product should be available and the effect of travel distances on the demand. The main goal is to understand better the dynamics of the system and to develop new models and extend existing ones in order to show the implications of combining marketing diffusion models and location decisions. I suggest 4 directions of research. 
 Queuing-Location Models: In the class of models we focus on, customers generate a stochastic stream of demands, servers have limited capacity, service times are stochastic and therefore customers arriving at the facilities must wait sometimes or leave the facility. The goal is to design a system where the main decisions are: number of facilities, their locations, their service capacities and the assignment of customers to facilities. I suggest 7 directions of research that aim at helping service managers improve system quality. 
 Inventory-Location Models: Traditionally optimal management of supply chain problems and location problems were studied separately. As this usually may lead to inefficiencies and high costs, we plan to consider them jointly. The main decisions include finding the number of facilities (suppliers, retailers and distribution centers (DCs)), their locations and the amount of inventory to order. I propose 5 directions of research that aim at gaining a better understanding of joint inventory and location decisions. We also anticipate contribution to the methodologies of both areas separately. 
We note that some of the issues considered in this proposal such as reducing waiting times (e.g., in healthcare) and locating reliable facilities are important in Canada., agreement title english : Combined Location Models, agreement title french : Combined Location Models, agreement number : RGPIN, agreement value : 255000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada