DNA sequence assembly problem is a very complex problem of computational biology. DNA sequence assembly is a NP hard problem there is no single solution available for this kind of problems. DNA sequence assembly refers to aligning and merging fragments of a much longer DNA sequence in order to reconstruct the original sequence. In this paper a solution is proposed for DNA sequence assembly prob...

In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibility, called PTAS-reducibility, introduced in a previous paper. As a rst application of this generalization, we prove the APX-completeness of a polynomially bounded optimization problem, that is, an APX problem whose measure function is bounded by a polynomial in the length of the instance and such...

Recent studies on a computationally hard visual optimization problem, the Traveling Salesperson Problem (TSP), indicate that humans are capable of finding close to optimal solutions in near-linear time. The current study is a preliminary step in investigating human performance on another hard problem, the Minimum Vertex Cover Problem, in which solvers attempt to find a smallest set of vertices ...

In cloud computing tasks scheduling problem is NP-hard, furthermore it does onerous for attaining an optimum resolution. Extremely quick optimization algorithms are used to proximate the optimum resolution, like ACO (ant colony optimization) algorithm. In cloud computing, in consideration to solve the problem of task scheduling, a period ACO (PACO)-based arranging algorithmic rule has been used...

Travelling Salesman Problem (TSP) is a classical combinatorial optimization problem. This problem is NP-hard in nature. Meta-heuristic approaches have proved to be quite useful for approximate solution of difficult combinatorial optimization problems. Ant colony optimization is one of the popular Meta-heuristics and is unique on the basis of its distributed computation and indirect communicatio...

We analyze the complexity status of one of the known discrete optimization problems where the optimization criterium is switched from max to min. In the considered problem, we search in a finite set of Euclidean vectors (points) a subset that minimizes the squared norm of the sum of its elements divided by the cardinality of the subset. It is proved that if the dimension of the space is a part ...

This paper describes a generic (meta-)cooperative optimization schema in which several agents endowed with an optimization technique (whose nature is not initially restricted) cooperate to solve an optimization problem. These agents can use a wide set of optimization techniques, including local search, population-based methods, and hybrids thereof, hence featuring multilevel hybridization. This...

Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST). In this paper we combine variable neighborhood search and accurate mixed integer programming (VNS-MIP) to solve MICLSP-TW-ST. It concerns so a particularly important and difficult problem in production planning. ...

Real World is filled with various hard and complex problems. One such complex problem is an optimization problem. Optimization has been an active area of research for several decades. . Optimized solutions are hard to find so there are no deterministic algorithms that can find exact solution in polynomial time. In large domain of applications of intelligence techniques we are interested in expl...

With the development of databases in general and data warehouses in particular, it is now of a great importance to reduce the administration tasks of data warehouses. The materialization of views is one of the most important optimization techniques. The construction of a configuration of views optimizing the data warehouse is an NP-hard problem. On the other hand, the algorithm called extremal ...