Research Article
A Hybrid Genetic Algorithm for the Multiple Crossdocks Problem
Algorithm 1
HGA to solve problem (
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Generate initial solutions by two-stage greedy method. | for to #maximum_iter do | for to #crossover do | Randomly select Parent 1 and Parent 2. | Crossover Parent 1 and Parent 2 to produce a new Offspring. | end for | for each offspring do | Mutate offspring with individual mutation probability and gene mutation probability | | Apply neighborhood search to each newly-produced Offspring. | end for | Select the best from all the Individuals including all current parents and | newly produced offsprings. | Update current best solution. | if the best solution could not improve within then | Consider the solution as the goal optimal solution. | break | end if | end for | output the best solution and escaped time |
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