In this paper, the surface approximation using a mesh optimization approach is investigated. The mesh optimization problem is how to locate a limited number n of grid points such that the established mesh of n grid points approximates the digital surface of N points as closely as possible. The resultant combinatorial problem has an NP-hard search space of C(N, n) instances, i.e., the number of ...

This paper investigates a well-known complex combinatorial problem known as the vehicle routing problem with time windows (VRPTW). Unlike the standard vehicle routing problem, each customer in the VRPTW is served within a given time constraint. This paper solves the VRPTW using an improved artificial bee colony (IABC) algorithm. The performance of this algorithm is improved by a local optimizat...

This paper presents a feasibility-preserving crossover and mutation operator for evolutionary algorithms for constrained combinatorial problems. This novel operator is driven by an adapted Pseudo-Boolean solver that guarantees feasible offspring solutions. Hence, this allows the evolutionary algorithm to focus on the optimization of the objectives instead of searching for feasible solutions. Ba...

The traveling salesman problem with precedence constraints (TSPPC) is one of the most difficult combinatorial optimization problems. In this paper, an efficient genetic algorithm (GA) to solve the TSPPC is presented. The key concept of the proposed GA is a topological sort (TS), which is defined as an ordering of vertices in a directed graph. Also, a new crossover operation is developed for the...

Genetic Algorithms are employed to optimize the selection of chiller size in a multi-chiller central plant for arbitrary cooling load profiles. The objective of the optimization is to minimize life cycle (capital + operating) costs while keeping all chillers running in good part load conditions to avoid any surge of chillers. The approach has the capability of solving the combinatorial optimiza...

Iterated local search (ILS) is a powerful meta-heuristic algorithm applied to a large variety of combinatorial optimization problems. Contrary to evolutionary algorithms (EAs) ILS focuses only on a single solution during its search. EAs have shown however that there can be a substantial gain in search quality when exploiting the information present in a population of solutions. In this paper we...

A recent and very promising approach for combinatorial optimization is to embed local search into the framework of evolutionary algorithms. In this paper, we present such hybrid algorithms for the graph coloring problem. These algorithms combine a new class of highly specialized crossover operators and a well-known tabu search algorithm. Experiments of such a hybrid algorithm are carried out on...

Architecture. The development of a flexible very-large-scale integration (VLSI) for GA has been proposed in this paper. For the hardware architecture, we has develop on a random number generator (RNG), crossover, and mutation based on flexibility structure. This structure can dynamically perform to the 3 types chromosome encoding: binary encoding, real-value encoding, and integer encoding. The ...

Memetic Algorithms have been proven to be successful to find the nearest optimum solution to hard combinatorial optimization problems. In this paper, Memetic algorithm is designed for Asymmetric Traveling salesman problem (ATSP). Memetic Algorithm is a combination of power of Genetic algorithm with the powerful local search technique to focus on the population of local optima. Because of perfor...