Optimization of Metro Trains Operation Plans Based on Passenger Flow Data Analysis

Algorithm 1

Mapper.

	Input: < key, value >, where the key is individual in one population, and the value is fitness in one population.
	Output: < key′, value′ >, where key′ is the best individual in the iterative process, and value′ is the best fitness value individual to key′.
	Algorithm Procedure:
(1)	Identify the number of iterations as M.
(2)	Initiate integer i = 0.
(3)	While(i < M):
	Compute individual fitness;
	Compute individual cumulative probability;
	Select;
	Crossover;
	Mutation;
	i++;
	End while
(4)	Compute individual fitness;
(5)	Find the best chromosome and fitness;
(6)	Output the chromosome and fitness;