Given an undirected graph with edge weights, the MAX-CUT problem consists in finding a partition of the nodes into two subsets, such that the sum of the weights of the edges having endpoints in different subsets is maximized. It is a well-known NP-hard problem with applications in several fields, including VLSI design and statistical physics. In this paper, a greedy randomized adaptive search p...

We consider the Nelder-Mead (NM) simplex algorithm for optimization of discrete-event stochastic simulation models. We propose new modifications of NM to reduce computational time and to improve quality of the estimated optimal solutions. Our means include utilizing past information of already seen solutions, expanding search space to their neighborhood and using adaptive sample sizes. We compa...

This paper presents a Greedy Randomized Adaptive Search Procedure (GRASP) for the Prize-Collecting Covering Tour Problem (PCCTP), which is problem of finding route traveling teams that provide services to communities geographically distant from large urban locations. We devised novel hybrid heuristic by combining reactive extension GRASP with Random Variable Neighborhood (VND) meta-heuristic pu...

due to the fact that the error surface of adaptive infinite impulse response (iir) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. in this case, global optimization techniques are required in order to avoid the local minima. harmony search (hs), a musical inspired metaheuristic, is a recently ...

Because of wake effects and geographical constraints, the search for optimal positions of wind turbines has an important part to play for their efficiency. The determination of their positions can be treated as optimization problem and can be solved by various methods. In this paper, we propose optimization approaches based on Simulated Annealing (SA) to improve solutions for the wind turbines ...

We propose and describe a hybrid GRASP with weight perturbations and adaptive path-relinking heuristic (HGP-PR) for the Steiner problem in graphs. In this multi-start approach, the greedy randomized construction phase of a GRASP is replaced by the combination of several construction heuristics with a weight perturbation strategy that combines intensification and diversification elements, as in ...

We propose and describe a hybrid GRASP with weight perturbations and adaptive path-relinking heuristic (HGP-PR) for the Steiner problem in graphs. In this multi-start approach, the greedy randomized construction phase of a GRASP is replaced by the combination of several construction heuristics with a weight perturbation strategy that combines intensification and diversification elements, as in ...

This paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the d...

To effectively solve the permutation flow-shop scheduling problem (PFSP), an adaptive dynamic neighborhood crow search algorithm (AdnCSA) is proposed to minimize makespan. Firstly, a modified heuristic based on nawaz-enscore-ham (NEH) was improve quality and diversity of initial population. Secondly, smallest-position-value (SPV) rule used encode population so that it can handle discrete proble...

The maximally diverse grouping problem (MDGP) is a relevant NP-hard optimization with number of real-world applications. However, solving large instances the computationally challenging. This work dedicated to new heuristic algorithm for problem, which distinguishes itself by two original features. First, it introduces first neighborhood decomposition strategy accelerate examinations. Second, i...