Most of the real-life applications have many constraints and they are considered as constrained optimization problems (COPs). In this paper, we present a new hybrid genetic differential evolution algorithm to solve constrained optimization problems. The proposed algorithm is called hybrid genetic differential evolution algorithm for solving constrained optimization problems (HGDESCOP). The main...

In this paper, we propose a genetic algorithm, called GenSPN, for finding highly probable differential characteristics of substitution permutation networks (SPNs). A special fitness function and a heuristic mutation operator have been used to improve the overall performance of the algorithm. We report our results of applying GenSPN for finding highly probable differential characteristics of Ser...

This research deals with a hybrid flow shop scheduling problem with parallel batching, machine eligibility, unrelated parallel machine, and different release dates to minimize the sum of the total weighted earliness and tardiness (ET) penalties. In parallel batching situation, it is supposed that number of machine in some stages are able to perform a certain number of jobs simultaneously. First...

Based on 3-D elasticity approach, differential quadrature method (DQM) in axial direction is adopted along with Globalized Nelder–Mead (GNM) algorithm to optimize the stacking sequence of a laminated cylindrical shell. The anisotropic cylindrical shell has finite length with simply supported boundary conditions. The elasticity approach, combining the state space method and DQM is used to obtain...

In this paper we present the current status of a method, first introduced in 2001 authored by J.-L. Lions, Y. Maday and G. Turinici that allows for parallization in time for the simulation of systems of Ordinary Differential Equations or time dependent partial differential equations. Following the same strategy as the one that is used in domain decomposition methods for solving elliptic problem...

In this paper, a constrained mean-variance model is constructed for the portfolio optimization problems. The model is a mixed quadratic integer programming problem, and it is too hard to solve by using the traditional optimal algorithms. The purpose of this paper is to use a heuristic algorithm to solve this problem. Combined with the differential evolution strategy, a new hybrid artificial bee...

Search is one of the most frequently used problem solving methods in artificial intelligence (AI) [1], and search methods are gaining interest with the increase in activities related to modeling complex systems [2, 3]. Since most practical applications involve objective functions which cannot be expressed in explicit mathematical forms and their derivatives cannot be easily computed, a better c...