the robust coloring problem (rcp) is a generalization of the well-known graph coloring problem where we seek for a solution that remains valid when extra edges are added. the rcp is used in scheduling of events with possible last-minute changes and study frequency assignments of the electromagnetic spectrum. this problem has been proved as np-hard and in instances larger than 30 vertices, meta-...

The paper attempts to solve the generalized “Assignment problem” through genetic algorithm and simulated annealing. The generalized assignment problem is basically the “N menN jobs” problem where a single job can be assigned to only one person in such a way that the overall cost of assignment is minimized. While solving this problem through genetic algorithm (GA), a unique encoding scheme is us...

Research on genetic algorithms (GAs) has shown that the initial proposals are incapable of solving hard problems in a robust and efficient way. Usually, for large-scale optimization problems, the execution time of first-generation GAs increases dramatically whereas solution quality decreases. The aim of this paper is to point out the main design issues in tailoring Simulated Annealing and GAs t...

Automatic text summarization is a process to reduce the volume of text documents using computer programs to create a text summary with keeping the key terms of the documents. Due to cumulative growth of information and data, automatic text summarization technique needs to be applied in various domains. The approach helps in decreasing the quantity of the document without changing the context of...

Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative...

Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative...

achieves the searching not only globally, but also locally. To keep general purpose, self-control processing by a handshake system is introduced. By adopting the handshake system, the proposed architecture can be applied to various combinatorial optimization problems by only changing an encoder, a decoder, and an evaluation circuit. Furthermore, the proposed architecture realizes flexibility fo...

The third component introduced in conventional turbo codes in recent days is effective in improving the performance of the code. But under noisy environments the parameters such as permeability and permittivity rates are static and hence their adapatability to noisy environment is poor. To overcome the aforesaid drawback A3D-TC was proposed in our previous paper[29].In our present paper a compa...

Many heuristics, such as simulated annealing, genetic algorithms, greedy randomized adaptive search procedures are stochastic. In this paper, we propose a deterministic heuristic algorithm, which is applied to the quadratic assignment problem. We refer this algorithm to as intensive search algorithm (or briefly intensive search). We tested our algorithm on the various instances from the library...