# Genetic algorithm gives same result everytime

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Gauri il 21 Feb 2024
Commentato: Gauri il 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.
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Walter Roberson il 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

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### Risposta accettata

Walter Roberson il 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.
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Gauri il 21 Feb 2024
oh
thank you

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