Development of a Nonlinear Integer Optimization Model for Tenant Mix Layout in a Shopping Centre

Table 2

Algorithm flow.

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Input information about the shopping centre to be laid out

Initialize the tenant layout population under logical constraints

Set parameters of the GA

Do

 For each iteration

 Calculate the fitness of all individuals in the population

  Find and then save the best solution and elite individuals in this generation into the next generation population

  Use the roulette method to select the individuals who can enter the next iteration

  The selected individual genes are crossed and mutated under logical constraints

  Update the population

 End

Until default number of iterations

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