This paper discusses the scheduling of Air Canada's planes across a network of cities. Where and when to fly planes are decisions faced by airlines worldwide. The two models used here were able to produce a daily schedule for seven Air Canada planes flying between seven cities, that optimizes profit levels. The obtained schedules are found to be very reasonable.

Metro Vancouver has an ever rapidly growing population. This combined with severe summer droughts that are increasing in frequency give rise to the need for radical change in Metro Vancouver's water distribution systems. In this project, these systems are examined, various network models are looked at in detail and various potential solutions are provided in order to help improve the current state of Metro Vancouver's water systems. The main goal of this examination is to minimize the need to acquire water from expensive sources and attempt to maximize the coverage of current water sources across Metro Vancouver. Four different models are constructed for this task as well as three different potential networks for Metro Vancouver.

We study the problem of scheduling employees at a local coffee house which has multiple (3) locations. Our model optimizes three conditions:

• Staff salary costs to be minimized
• Employee satisfaction maximized
• Staff scheduling requirements should be met as closely as possible

The cost of staff is based on the number of employees in each level of employment at the various cafes. We assume two types of employees, baristas and managers, which have specific hourly wages.
Satisfaction of employees is based on their location preference and their preferred number of hours to work each week. Workers can work at any of the three cafes. Each shift has a preferred amount of employees which we try to match as closely as possible.

Retail stores employ a large amount of full time and part time employees. With the addition of many different departments, making efficient schedules can be a challenge. In this paper, we will develop a binary integer programming problem which will be used to minimize the total employee cost, while ensuring proper employee coverages.

This paper proposes and solves a modified allocation problem that aims to implement the Bike Sharing Program. Here, we seek to maximize the total benefit of each bike station while minimizing the total operational cost. Through this two-step process, various optimization methods are used to (a) determine the most optimal bike stations among all candidate locations, and (b) decide on the most optimal number of bikes needed for each station. Considering the constraints imposed by the software used in this project, Microsoft Excel, the problem is limited to selecting four stations among 14 different candidate locations. We determine the optimal number of bikes at the beginning of the day at each location.

Food trucks offer an exciting alternative to eating out while tailoring to the fast-paced lifestyle of city dwellers, but effective methods to implement this form of dining-out alternative are still non-existent to many cities where it is a new concept. Cannibalism of local restaurants can occur when food trucks are licensed without informal planning. The conflict between local restaurants and food trucks has been a recurring theme in the media in recent times; the City of Vancouver is now seeking better methods to find optimal locations for the food trucks.
In this paper, we develop discrete optimization models for this problem and solve the model using Open-Solver, an Excel-based optimization engine. The data collected for this paper includes pedestrian data, active food trucks in the year 2012, road information, and licensed restaurants in downtown Vancouver. Our study indentified optimal locations for the summer of 2013. Various alternative formulations are also given and a comparative study is performed. While our paper concentrates on the city of Vancouver, the model is general enough to be applicable to other cities that are starting to implement food truck alternatives.

The university selection problem deals with finding an optimal choice of courses from a set of alternatives to attain a prescribed goal for the student's program of choice. It is assumed that a timetable is already given. If the planning is done for a term, the problem is simple and can be solved by complete enumeration using a computer. For multi-year planning, complete enumeration is impractical. The problem is made more complicated when inter-campus travel is also involved.
In this paper we formulate the selection problem as a maximum weight independent set problem with specially structured additional constraints. Data for the experiments are collected from the SFU student information system. Experimental results using a general purpose integer programming solver is given. Our model could easily solve the problem, producing an optimal solution in very reasonable running times.

Currently, the intuitive greedy algorithm is generally used for appointment scheduling in health care facilities, such as dental clinics. We look into another approach, which is based on statistical data, develop the algorithm that optimizes the scheduling process, benefiting both the facility and its customers, and then test it on the historical data using simulation (work in progress). Positive results of the simulation will indicate that the algorithm is more efficient than the original greedy algorithm, which potentially allows us to implement it in the form of a scheduling software for the variety of health facilities in Canada.

The recent addition of a toll on the Port Mann Bridge in Greater Vancouver has resulted in an observed increase in traffic volumes on alternate routes crossing the Fraser River. The result has been lower than expected volumes on the Port Mann Bridge and increased congestion on other major arteries in the region. The paper describes in the development of a mathematical programming model to determine an optimal tolling system for the four main Fraser River crossings; the Port Mann, Alex Fraser and Putullo bridges and the Massey tunnel. Two scenarios are discussed, starting with the current situation of one toll on the Port Mann Bridge, while a second will open the possibility of implementing a toll on all four crossings. The intention is to minimize congestion in the region through the redistribution of traffic.

Telecommunications service providers are competing in an environment where the pervasive nature of mobile technology requires them to establish an improved network system with wider coverage and a stronger signal to satisfy the escalating demand. The telecommunication equipment problem if formulated as a combination of maximal coverage and assignment problems, and is solved using CPLEX, Excel, and R. The objective is to station devices in locations where the largest number of consumers are able to enjoy desired services, while considering various demands including population density, points of interest, average household income, age, transit ridership, and the location of existing towers.

Canada Post has recently decided to phase out door-to-door delivery in urban areas in favour of building community mailboxes. This change in delivery method will require all households to walk to their nearest community mail box (CMB). Since operations costs will now largely be dependent on transportation costs, we aim to find locations for community mailboxes while also planning routes for the delivery of mail to these boxes. The purpose of the community mailbox location-routing problem is to place a minimal number of CMBs within a reasonable walking distance to each house, and find the shortest route for delivery. Our model uses a combination of heuristic methods including clustering and the sequential use of the allocation problem and travelling salesman problem. We obtained successful results applying our model to a small neighbourhood in Delta, BC, on a single test cluster.

The cross streets of W. Broadway and Cambie is one of the busiest intersections in the Vancouver metropolitan area. Introducing a new traffic pattern, such as a diagonal crossing (scramble crossing), to improve pedestrian crossing efficiency can be risky considering the high traffic volume that this traffic corridor supports. The benefits from introducing a scramble crossing include the obvious shorter distance travelled by pedestrians when wanting to reach an opposite corner, and, given the right type of scramble crossing, a reduction in vehicle delays that are produced by walking pedestrians. Based on research and a review previous studies and methods, we constructed a mixed integer programming model to establish if the introduction of a scramble crossing at the chosen intersection would improve efficiency. Applying our model to the intersection of study generated positive results, allowing us to recommend that a scramble intersection be introduced.

We consider the problem of scheduling teaching assistants (TAs) in an open tutorial lab. Open tutorials provide an integrated framework of offering tutorials for multiple courses. Hence, the assignment of teaching assistants raises several optimization challenges. We formulate the TA assignment problem as a minimization-cost network flow model with additional restrictions to distribute the tutorial workload among several TAs. Factors such as TA availability, course schedules, and expected student turnout are taken into account. The model takes advantage of certain jobs that do not require specific time scheduling. The output of the model yields a solution that can reach the most students possible. Furthermore, since these are generally small problems, solutions can be found in a timely manner using a general purpose integer programming solver such as Excel.

Universities typically have a set schedule when classes are offered, and a pool of classrooms of various sizes to match to these classes. Unlike other academic scheduling problems (e.g., when to schedule classes or examinations), we will hold the schedule constant and only optimize the allocation of the rooms. We provide a background of research already published, the basic three-dimensional integer linear problem, the problem with reduced dimensions, and a reformulation into a linear transportation program. We specifically look at the case study of Simon Fraser University, Surrey.

This paper proposes and solves a modified diet problem that looks at the consumption of food from a larger perspective. Here we try to maximize the nutrient intake of an individual, as well as their preference for not eating the same food for every meal and minimizing the cost of purchasing their food. This problem was formulated as a linear program and solved using Open Solver in Microsoft Excel.

We consider the specific diet problem, which comes from a real life situation: an average student chooses a two week diverse lunch plan based on food available on campus. A mixed integer programming model is used to find an optimal lunch plan, so that the daily recommended intake of nutrients is satisfied and consumption of harmful nutrients is minimized. The results obtained for a specific case of the SFU Surrey campus were found to be very reasonable.