Project Selection

ProjectSelectionProblem

Description

Defines the project selection problem.

Fields

• cost::Matrix: A matrix where each row represents a project and each column represents a resource. The values in the matrix represent the cost of using that resource for that project.
• budgets::Vector: A vector where each element represents the budget available for the corresponding resource.
• returns::Vector: A vector where each element represents the return of selecting the corresponding project.

ProjectSelectionResult

Description

A structure to hold the result of the project selection problem.

Fields

• selected: A vector of booleans (0 and 1s) indicating which projects are selected.
• objective: The objective value of the model.
• model: The JuMP model used to solve the problem.

solve(problem::ProjectSelectionProblem)::ProjectSelectionResult

Description

Solves the project selection problem using JuMP and HiGHS.

Arguments

• problem::ProjectSelectionProblem: The project selection problem to be solved.

Returns

• ProjectSelectionResult: The result of the project selection problem.

Example

# Project 1 requires 3M, 5M, and 6M dollars for years 1, 2, and 3 respectively, and returns 10M dollars.
# Project 2 requires 2M, 4M, and 5M dollars for years 1, 2, and 3 respectively, and returns 12M dollars.
# Project 3 requires 5M, 4M, and 2M dollars for years 1, 2, and 3 respectively, and returns 15M dollars.
# etc.
# The budgets for years 1, 2, and 3 are 8M, 9M, and 6M dollars respectively.
# What projects should be selected to maximize returns?
costmatrix = [
    3 5 6;
    2 4 5;
    5 4 2;
    2 1 5;
    8 9 6;
]
returns = [10, 12, 15, 8, 200]
budgets = [8, 9, 6]
problem = ProjectSelectionProblem(costmatrix, budgets, returns)
result = solve(problem)
println("Selected projects: ", result.selected)
println("Objective value: ", result.objective)