Solving the Graph Planarization Problem Using an Improved Genetic Algorithm
نویسندگان
چکیده
An improved genetic algorithm for solving the graph planarization problem is presented. The improved genetic algorithm which is designed to embed a graph on a plane, performs crossover and mutation conditionally instead of probability. The improved genetic algorithm is verified by a large number of simulation runs and compared with other algorithms. The experimental results show that the improved genetic algorithm performs remarkably well and outperforms its competitors. key words: graph planarization problem, NP-complete problem, genetic algorithm
منابع مشابه
Solving the ridesharing problem with Non-homogeneous vehicles by using an improved genetic algorithm and the social preferences of the users
Most existing ridesharing systems perform travel planning based only on two criteria of spatial and temporal similarity of travelers. In general, neglecting the social preferences caused to reduce users' willingness to use ridesharing services. To achieve this purpose a system should be designed and implemented not just based on two necessary conditions of spatial and temporal similarities, but...
متن کاملSolving a nurse rostering problem considering nurses preferences by graph theory approach
Nurse Rostering Problem (NRP) or the Nurse Scheduling Problem (NSP) is a complex scheduling problem that affects hospital personnel on a daily basis all over the world and is known to be NP-hard.The problem is to decide which members of a team of nurses should be on duty at any time, during a rostering period of, typically, one month.It is very important to efficiently utilize time and effort, ...
متن کاملAn Effective Genetic Algorithm for Solving the Multiple Traveling Salesman Problem
The multiple traveling salesman problem (MTSP) involves scheduling m > 1 salesmen to visit a set of n > m nodes so that each node is visited exactly once. The objective is to minimize the total distance traveled by all the salesmen. The MTSP is an example of combinatorial optimization problems, and has a multiplicity of applications, mostly in the areas of routing and scheduling. In this paper,...
متن کاملAn improved genetic algorithm for multidimensional optimization of precedence-constrained production planning and scheduling
Integration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial,...
متن کاملA reactive bone route algorithm for solving the traveling salesman problem
The traveling salesman problem (TSP) is a well-known optimization problem in graph theory, as well as in operations research that has nowadays received much attention because of its practical applications in industrial and service problems. In this problem, a salesman starts to move from an arbitrary place called depot and after visits all of the nodes, finally comes back to the depot. The obje...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEICE Transactions
دوره 89-A شماره
صفحات -
تاریخ انتشار 2006