This story is more about mathematics so a bit hard but keep try it's not too hard so
Starting with simple OR stand for Operation Research
What can we make the thing
Optimize under constraints condition
Heuristics : exact the problem and find the exact solution by using algorithm
example : Simulated Annealing for physic
Metaheuristics: nearly optimize solution
Random search waste time and not guarantee the solution
next is airline hub and floor layout what is make sense to be use as a hub by planing or layout under condition time and less energy and other condition if in floor. size is matter for this condition
Critical terms
Optimize Problem: What is Objective function and Quality that call fitness.
F(X1 + X2 + X3 )= X1*P2+ X2*P2 +X3*P3
F = FITNESS VALUE
X1, X2, X3 = DECISION VARIABLE
search space
constraints = ข้อจำกัด
boundary = ขอบเขต
min f(x,y) where f(x,y) = x^2 + y^2 , where x,y E [-10,10]
D = Dimension , Dimenallity = number of variable
The number of variables
- univariate problem = 1 var
- multivariate problem = 2 or more
Degree of nonlinearity of the obj function:
- Linear = f=x+y
- Quadratic = (x+y)^2 this is power 2
- Nonlinear = other power that not 2 is all non linear
Type of variables
- Continuous problem ex: xi E R
- Discrete or integer opt problem ex: xi E T
- Mixed opt problem
- Combinatorial opt problem = swap the way of point ar like shuffle the way to make the opt way that fix problem the best other like is traveling salesman, vehicle routing problem or nurse/ guard schedule.
More constrain problem
equality and inequality Feasible region like X1+X2+X3 <= 10 OR 3X1 + X3 <=24
more condition more boundary constraint that make search space or feasible region is less more that good
MySimpleDiary
Continue to part 2
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