Abstract: Since the development of web, we can use various type data such as movie, music, and social network data. These data is very useful to make recommendation system. For this reason, several recommendation system studies used the web data to construct outstanding system. In this paper, we proposed a method to recommend combinations of appointment places based on web data. Our system generates ranking to extract best store, and use location data to recommend suitable store. By considering these two main features, the proposed system recommend best and suitable store to user to recommend combinations of appointment places. Our system provides a chance to design combinations of appointment places with highquality easily

• Publication Date: 29-Aug-2015
• DOI: 10.15224/978-1-63248-073-6-23
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• Downloads: 0

Abstract: Traveling salesman problem is of the known and classical problems at Research in Operations. Many scientific activities can be solved as traveling salesman problem. Existing methods for solving hard problems (such as the traveling salesman problem) consists of a large number of variables and constraints which reduces their practical efficiency in solving problems with the original size. In recent decades, the use of heuristic and meta-heuristic algorithms such as genetic algorithms is considered. Due to the simple structure of metaheuristic algorithms that have shown greater ability is more used by researchers in operational research. In this study, the improved genetic algorithm is used to solve TSP that the difference of it with the standard genetic algorithm is in the evaluation function. The new evaluation function is from a common evaluation function and a new idea.

• Publication Date: 29-Aug-2015
• DOI: 10.15224/978-1-63248-073-6-24
• Views: 0
• Downloads: 0