cuckoo search algorithm

In this paper, a new machine and vehicle simultaneous scheduling model has been developed taking into account the feasibility of transport, and the dependence of transport time on the type of work, considering the stopping time of the machine and its repair time, which is compatible with the industry environment. To find the answer, the multi-objective cuckoo search algorithm has been developed and for comparing and testing its efficiency, two other algorithms with the same structure have been used. The results obtained by the developed multi-objective cuckoo search algorithm were compared with other algorithms and the results show the superior quality of the solutions of the developed multi-objective cuckoo search algorithm for solving this type of problem. Therefore, using this new problem with the proposed solution method in the industrial environment will simultaneously reduce processing costs and increase the level of product quality and increase the level of customer service.

The main objective of this study is to present a pattern for standard summarization of Persian texts with the approach of converting the problem to optimization problem by compatible meta-heuristic algorithms. In this research, standard multi-text "Pasokh" collection, which contains 50 different types of news from the most popular news agencies in Iran, each containing 20 documents, as well as 5 summaries of abstractive and 5 extractive, used for evaluation. First, the preprocessing performed on the input texts and the initial summary generated with TF-ISF benchmark, readability and consistency criteria of the sentences, similarity to the title, position of the sentence in the text, and the length of the sentence. With respect to each of these criteria, weighting function assigned to extracted sentences and a similarity matrix created. Then, output of the extraction system processed by Genetic algorithm and Cuckoo search algorithm for the final summary. Eventually, the output obtained from the previous step analyzed using the Rouge evaluation tools and the comparison with the human abstracts. The average of all values obtained in Rouge evaluation tools for calculation the overlapping of common samples of human summaries and machine summaries by Cuckoo search algorithm were higher than the values obtained by Genetic algorithm as well as Ijaz online summarizer system. Meanwhile, among the eight criteria, the longest common sub-sentence with a value of 0.33 and the number of common words in the text with 0.40 were better than the rest. The results of the comparison of two algorithms indicate that the Cuckoo search algorithm is better in the entire criteria. On the other hand, comparing the results suggests that the average time calculated for summarizing by the proposed system is also less.