# Genetic algorithm gives same result everytime

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Gauri on 21 Feb 2024
Commented: Gauri on 21 Feb 2024
Hello,
I'm trying to minimise total cost of inventory incurred by a bread retailer, by optimising the maximum inventory level. Im using genetic algorithm. The output that i need to record is the maximum inventory level and Total cost. atleast 5 entries.
My problem is that after running the genetic algorithm multiple times, it is giving the same results. Is there a problem with my code? It is attached below.
objective function is 'totalcost'. Accessory to it is 'inventoryupdate'.
Genetic algorithm is in 'check2'. It was made using optimiser task insert.
Walter Roberson on 21 Feb 2024
check2
OptimizationProblem : Solve for: maxS where: maxS integer minimize : totalCostFunction(maxS) variable bounds: 10 <= maxS <= 100 Solving problem using ga. ga stopped because the average change in the penalty function value is less than options.FunctionTolerance and the constraint violation is less than options.ConstraintTolerance.
solution = struct with fields:
maxS: 45
reasonSolverStopped =
SolverConvergedSuccessfully
objectiveValue = int32 32520
check2
OptimizationProblem : Solve for: maxS where: maxS integer minimize : totalCostFunction(maxS) variable bounds: 10 <= maxS <= 100 Solving problem using ga. ga stopped because the average change in the penalty function value is less than options.FunctionTolerance and the constraint violation is less than options.ConstraintTolerance.
solution = struct with fields:
maxS: 45
reasonSolverStopped =
SolverConvergedSuccessfully
objectiveValue = int32 32520

Walter Roberson on 21 Feb 2024
You have a single variable that is integer constrained between 10 and 100. That is only 91 different values to search, at most -- and the search is guided by the function values.
The problem is just simple enough that you always get the same answer in practice.
Gauri on 21 Feb 2024
oh
thank you

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