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| Cardinal of a given set. |
| Relative importance of pheromone trails, . |
| The set of columns that row covers, . |
| Binary matrix of m-rows and n-columns. The rows are the elements of the universe and the columns are the subsets . |
| Percentage of columns to be added during the generation of a solution in ABC. |
| Percentage of columns to be removed during the generation of a solution in ABC. |
| Heuristic factor of column at step for the alternative formulation, . |
| Value in the cell of . It equals 1 if the -th column covers the -th row and 0 otherwise, , . |
| Point/points in which a function gets its maximum value/values. |
| Point/points in which a function gets its minimum value/values. |
| The sum of the gains of covering the noncovered rows which could be covered by column at . |
| Relative importance of heuristic information, . |
| Set of costs, . |
| Heuristic factor of column at step for the classical formulation, . |
| Cost associated to the -th column, . |
| Cost of the cheapest set among the sets covering , , . |
| Number of noncovered rows which could be covered by column at step . |
| Solution generated by an ant at step , . |
| A solution to the problem, . |
| Ratio coefficient, . |
| Heuristic factor of column at step , . |
| Universe of elements, . |
| -th element of , , . |
| Average fitness evaluations needed for reaching the best solution found during the exploration. |
| Fitness function of the classical SCP formulation, . |
| Fitness function of the alternative SCP formulation, . |
| Gain of covering an element , , . |
| Row set, . |
| Row set covered by column , . |
| Percentage of improvement by considering the alternative approach of the algorithm instead of the default version. |
| Column set, . |
| The best solution found from the beginning of the algorithm, . |
| Threshold value based on trials for deciding if a worker bee is transformed into a scout one in ABC, . |
| Cardinal of or number of rows. |
| Cardinal of or number of columns. |
| Number of worker bees in ABC, . |
| Amount of pheromone put on column , . |
| Very small positive constant, . |
| Population size in ACO. |
| Population size in ABC. |
| Landscape solution quality metric, . |
| Random number uniformly distributed in . |
| Parameter determining the relative importance of exploitation versus exploration, . |
| Pheromone persistence, . |
| Set of unselected columns in , , . |
| Average RPD from a distribution, . |
| Average RPD of algorithm , with . |
| Average RPD of algorithm , with . |
| Average RPD of algorithm , with . |
| Average RPD of algorithm , with . |
| Minimum RPD from a distribution, . |
| Maximum RPD from a distribution, . |
| Set of subsets, , . |
| -th subset of , , , . |
| Landscape rate of success, . |
| Landscape speed of reaching a solution, . |
| Pheromone trail of column , . |
| Construction step in ACO, . |
| Average execution time of algorithm , with . |
| Average execution time of algorithm , with . |
| Average execution time of algorithm , with . |
| Average execution time of algorithm , with . |
| Number of uncovered rows in a solution, . |
| Set of uncovered rows in , , . |
| Number of columns in a solution that cover the row , . |
| An SCP solution expressed as binary vector, . |
| -th element of . It equals 1 if is part of the solution and 0 otherwise, . |
| Variable equaling 1 if the element is covered in and 0 otherwise, . |
| Column provided by SROM at step , . |
| Average cost obtained from a distribution, . |
| Maximum cost obtained from a distribution, . |
| Minimum cost obtained from a distribution, . |
| Optimum solution of a given instance, . |
| Column selected at step , . |
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