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Binary Integer Programming (Gear-512 Applications (Energy Distribution…
Binary Integer Programming
Concept
Variables
Restricted to be
either 0 or 1
N-th variables are taken in decision values
Main
Objective
Decision-making
Solving
Algorithms
Implicit Enumeration
Enumerate all solution
Analize every combination
Egon Bala's Method
Transform de problem
Positive coefficients in objective function
Minimize de function
Every constraint must be <=
Iterating
Table
Variables
Constraint comparisons
Infeasibility
Process
First row is 0 for every variable
Other rows consider one variable = 1
Infeasibility is added when any comparison doesn't correspond with the result obtained
The less feasible combination will remain in the next iteration for every combination
Repeat the process until one combination gets 0 infeasibility
Branch and Bound
Applications
Energy Distribution
Investment Analysis
Project Selection
Knapsack Problem
Plant Building
Multiple Traveling
Salesman Problem
Advantages
Problems may have
prompt solutions
Covers a wide range of Application Problems
Disadvantages
Branch and
Bound
Creates a considerable quantity of subproblems
May create
pointless branches
Implicit enumeration
Exponential
complexity
Software
WinQSB
Gurobi
IBM Cplex
Lingo
