Theory and algorithms for plan merging
Artificial Intelligence
On the Approximation of Shortest Common Supersequencesand Longest Common Subsequences
SIAM Journal on Computing
Journal of Computer and System Sciences - Special issue on Parameterized computation and complexity
Solving the sorting network problem using iterative optimization with evolved hypermutations
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A probabilistic beam search approach to the shortest common supersequence problem
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Iterative prototype optimisation with evolved improvement steps
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Memetic algorithms with partial lamarckism for the shortest common supersequence problem
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
A comparison of evolutionary approaches to the shortest common supersequence problem
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
On the Hybridization of Memetic Algorithms With Branch-and-Bound Techniques
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Black-box optimization benchmarking of two variants of the POEMS algorithm on the noiseless testbed
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Comparison of cauchy EDA and pPOEMS algorithms on the BBOB noiseless testbed
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Evolutionary-based iterative local search algorithm for the shortest common supersequence problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
An enhanced beam search algorithm for the Shortest Common Supersequence Problem
Engineering Applications of Artificial Intelligence
Hyper-Heuristic based on iterated local search driven by evolutionary algorithm
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
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The Shortest Common Supersequence (SCS) problem is a well-known hard combinatorial optimization problem that formalizes many real world problems. Recently, an application of the iterative optimization method called Prototype Optimization with Evolved Improvement Steps (POEMS) to the SCS problem has been proposed. The POEMS seeks the best variation of the current solution in each iteration. The variations, considered as structured hypermutations, are evolved by means of an evolutionary algorithm. This approach has been shown to work very well on synthetic as well as real biological data. However, the approach exhibited rather low scalability which is caused by very time demanding evaluation function. This paper proposes a new time efficient evaluation procedure and a new moving-window strategy for constructing and refining the supersequence. These two enhancements significantly improve an efficiency of the approach. Series of experiments with the modified POEMS method have been carried out. Results presented in this paper show that the method is competitive with current state-of-the-art algorithms for solving the SCS problem. Moreover, there is a potential for further improvement as discussed in the conclusions.