Moreover,the Block properties of FSP is introduced,with which the size of neighborhood is greatly reduced,and search is then focused on the promising area of the neighborhood,which enhance the performance more.

To the problem that it takes a long time for current available algorithms to solve large-scale flow shop scheduling problems(FSPs),a fast taboo search algorithm based on Block properties of FSP is proposed to reduce the neighborhood size.

The one-block property is stated and it is proved that, whenever it holds for a class closed under homomorphic images, it implies congruence semimodularity for the whole class.

An equational characterization of regular varieties having the one-block property is obtained.

Some characterization is obtained also for irregular varieties of semigroups having the one-block property.

Simulated annealing(SA) algorithm is one of the commonly used approaches in solving flow shop scheduling problems(FSPs).For the large-scale FSPs,the accepting probability of the candidate neighbor decreases greatly as the size of neighborhood and the number of bad neighbors increase,which leads to low performance of SA.A kind of simulated annealing algorithm based on the Block properties of FSP is proposed to solve the problem.In the proposed algorithm,the whole neighborhood is first divided into several small...

Simulated annealing(SA) algorithm is one of the commonly used approaches in solving flow shop scheduling problems(FSPs).For the large-scale FSPs,the accepting probability of the candidate neighbor decreases greatly as the size of neighborhood and the number of bad neighbors increase,which leads to low performance of SA.A kind of simulated annealing algorithm based on the Block properties of FSP is proposed to solve the problem.In the proposed algorithm,the whole neighborhood is first divided into several small sub-neighborhoods.The best neighbor in the whole sub-neighborhood is selected as the candidate neighbor so as to increase the accepting probability.Moreover,the Block properties of FSP is introduced,with which the size of neighborhood is greatly reduced,and search is then focused on the promising area of the neighborhood,which enhance the performance more.Numerical experiments show that the near-optimal solutions of large-scale FSPs can be found in a short time with the proposed algorithm.

To the problem that it takes a long time for current available algorithms to solve large-scale flow shop scheduling problems(FSPs),a fast taboo search algorithm based on Block properties of FSP is proposed to reduce the neighborhood size.With the Block properties,most bad solutions in the neighborhood are excluded without losing the optimal solution.The point of search is focused on the "most promising" area to reduce the size of neighborhood and running time.Numerical experiments show that good solutions of...

To the problem that it takes a long time for current available algorithms to solve large-scale flow shop scheduling problems(FSPs),a fast taboo search algorithm based on Block properties of FSP is proposed to reduce the neighborhood size.With the Block properties,most bad solutions in the neighborhood are excluded without losing the optimal solution.The point of search is focused on the "most promising" area to reduce the size of neighborhood and running time.Numerical experiments show that good solutions of large-scale FSPs are found in a short time with the proposed algorithm.