Research Article
A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production
Algorithm 2
PSOB algorithm main steps.
| initialsolution() | | 1, 20, 30, | | while do | | repeat | | select neighborhood operator | | for all solutions ’ that can be generated by applying to do | | if tardiness(’) < tardiness() then | | ’ | | end if | | end for | | until s is locally optimal for all operators | | update() | | + 1 | | end while | | BestSolution GlobalMin, Solution[] GlobalParas[] | | initialsolution(): 1, 20, 30, 1, 20 | | maxEpoch | | while do | | scouts: decode the particle to generate genes, obtain the reduced MIP and solve it by | | CPLEX | | calculate fitness | | generate employed bees and onlooker bees: trail() 0 | | select neighborhood operator | | for all solutions ’ that can be generated by applying to do | | if tardiness(’) < tardiness() then | | ’ | | trial()=0 | | else | | trial()=trail()+1 | | end if | | calculate Probability() | | if Probability() > rand() | | employed bees: select neighborhood operator | | for all solutions ’ that can be generated by applying to do | | if tardiness(’) < tardiness() then | | ’ | | trial() 0 | | else | | trial() trail()+1 | | end if | | end if | | if trail() > | | scouts: generate the new food source | | update BestSolution | | +1 | | end if | | if | | find BestSolution | | else | | generate employed bees and repeat | | end if | | end while |
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