Recommender systems detect users' favorites based on their past behavior and provide them with proper suggestions;however, these systems would encounter problems while dealing with users with low or empty usage da...
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ISBN:
(纸本)9781479980215
Recommender systems detect users' favorites based on their past behavior and provide them with proper suggestions;however, these systems would encounter problems while dealing with users with low or empty usage data. This issue leads to the most prominent challenge of such systems called cold start. In thispaper, we proposea system based on which a modified discrete imperialist competitive algorithm where tags are clustered using K-medoids algorithm. When a new user logs in and enters his/her tags then the system will suggest just a few sources with the largest weight. Experimental results demonstrate improvement of evaluation criteria for recommender system in comparison with other methods.
We study a location-allocation-routing problem for distribution of the injured in a disaster response scenario, considering a three-type transportation network with separate links. A circle-based approach to estimate ...
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We study a location-allocation-routing problem for distribution of the injured in a disaster response scenario, considering a three-type transportation network with separate links. A circle-based approach to estimate the impacts of the disaster is presented. After formulating relations for computing the percentage of the injured, the destruction percentage and the damage-dependent travel times, the problem is formulated as an integer nonlinear program. We utilize a genetic algorithm and a discrete version of the imperialistcompetitivealgorithm for solving large problems. An empirical study focused on earthquakes in Tabriz, Iran, illustrates applicability of the proposed model and performance of the proposed algorithms.
The imperialistcompetitivealgorithm (ICA) is a new heuristic algorithm proposed for continuous optimization problems. The research about its application on solving the traveling salesman problem (TSP) is still very ...
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The imperialistcompetitivealgorithm (ICA) is a new heuristic algorithm proposed for continuous optimization problems. The research about its application on solving the traveling salesman problem (TSP) is still very limited. Aiming to explore its ability on solving TSP, we present a discrete imperialist competitive algorithm in this paper. The proposed algorithm modifies the original rules of the assimilation and introduces the 2-opt algorithm into the revolution process. To examine its performance, we tested the proposed algorithm on 10 small-scale and 2 large-scale standard benchmark instances from the TSPLIB and compared the experimental results with that obtained by two other ICA-based algorithms and six other existing algorithms. The proposed algorithm shows excellent performance in the experiments and comparisons.
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