A modified version of a T‐Cell Algorithm for constrained optimization problems

In this paper, we present a heuristic inspired on the T‐Cell model of the immune system (i.e. an artificial immune system). The proposed approach (called T‐Cell) is used for solving constrained (numerical) optimization problems, and is validated using several test functions taken from the specialized literature on evolutionary optimization. Additionally, several engineering optimization problems are also used for assessing the performance of the proposed approach. The results are compared with respect to approaches representative of the state‐of‐the‐art in constrained evolutionary optimization. Copyright © 2010 John Wiley & Sons, Ltd.     

Handling constraints using multiobjective optimization concepts

In this paper, we propose a new constraint‐handling technique for evolutionary algorithms which we call inverted‐shrinkable PAES (IS‐PAES). This approach combines the use of multiobjective optimization concepts with a mechanism that focuses the search effort onto specific areas of the feasible region by shrinking the constrained search space. IS‐PAES also uses an adaptive grid to store the solutions found, but has a more efficient memory‐management scheme than its ancestor (the Pareto archived evolution strategy for multiobjective optimization). The proposed approach is validated using several examples taken from the standard evolutionary and engineering optimization literature. Comparisons are provided with respect to the stochastic ranking method (one of the most competitive constraint‐handling approaches used with evolutionary algorithms currently available) and with respect to other four multiobjective‐based constraint‐handling techniques. Copyright© 2004 John Wiley & Sons, Ltd.     

A hybrid Differential Evolution—Tabu Search algorithm for the solution of Job-Shop Scheduling Problems

The Job-Shop Scheduling Problem (JSSP) has drawn considerable interest during the last decades, mainly because of its combinatorial characteristics, which make it very difficult to solve. The good performances attained by local search procedures, and especially Nowicki and Smutnicki's i-TSAB algorithm, encouraged researchers to combine such local search engines with global methods. Differential Evolution (DE) is an Evolutionary Algorithm that has been found to be particularly efficient for continuous optimization, but which does not usually perform well when applied to permutation problems. We introduce in this paper the idea of hybridizing DE with Tabu Search (TS) in order to solve the JSSP. A competitive neighborhood is included within the TS with the aim of determining if DE is able to replace the re-start features that constitute the main strengths of i-TSAB (i.e., a long-term memory and a path-relinking procedure). The computational experiments reported for more than 100 JSSP instances show that the proposed hybrid DE–TS algorithm is competitive with respect to other state-of-the-art techniques, although, there is still room for improvement if the adequacy between the solution representation modes within DE and TS is properly stressed.     

Evolutionary Synthesis of Logic Circuits Using Information Theory

In this paper, we propose the use of Information Theory as thebasis for designing a fitness function for Boolean circuit designusing Genetic Programming. Boolean functions are implemented byreplicating binary multiplexers. Entropy-based measures, such asMutual Information and Normalized Mutual Information areinvestigated as tools for similarity measures between the targetand evolving circuit. Three fitness functions are built over aprimitive one. We show that the landscape of Normalized MutualInformation is more amenable for being used as a fitness functionthan simple Mutual Information. The evolutionary synthesizedcircuits are compared to the known optimum size. A discussion ofthe potential of the Information-Theoretical approach is given.     

Multiobjective optimization of trusses using genetic algorithms

In this paper we propose the use of the genetic algorithm (GA) as a tool to solve multiobjective optimization problems in structures. Using the concept of min–max optimum, a new GA-based multiobjective optimization technique is proposed and two truss design problems are solved using it. The results produced by this new approach are compared to those produced by other mathematical programming techniques and GA-based approaches, proving that this technique generates better trade-offs and that the genetic algorithm can be used as a reliable numerical optimization tool.     

Simultaneous multiwavelength spectrophotometric determination of 1:2 metal-complex dyes for leather

A spectrophotometric method for simultaneous determination of dyes has been developed. It is based on the resolution of a mixed spectrum over an appropriate wavelength range, by applying a least-squares fitting program to standard spectra for each component. The proposed method was applied to mixtures of 1:2 metal-complex dyes typically used by the leather industry. Four dyes were quantified simultaneously in less than a minute, with overall errors less than 2.5%     

Solving timetabling problems using a cultural algorithm

This paper addresses the solution of timetabling problems using cultural algorithms. The core idea is to extract problem domain information during the evolutionary search, and then combine it with some previously proposed operators, in order to improve performance. The proposed approach is validated using a benchmark of 20 instances, and its results are compared with respect to three other approaches: two evolutionary algorithms and simulated annealing, all of which have been previously adopted to solve timetabling problems.     

Changes produced in the aroma compounds and structural integrity of basil (Ocimum basilicum L) during drying

The influence of drying on the aroma compounds, from a chemical and sensory standpoint, and on the structural integrity of basil (Ocimum basilicum L) was evaluated. The drying methods tested were oven drying at 45 °C, air drying at room temperature and freeze‐drying. The volatile compounds of fresh and dried basil were extracted and concentrated by simultaneous distillation/extraction and analysed by gas chromatography/mass spectrometry. In all, 27 volatile components were identified, linalool being the major component, followed by eugenol. The total quantity of volatiles of fresh basil decreased considerably during oven drying and freeze‐drying, whereas air drying of basil at room temperature brought about only small losses of volatile components. The cell damage produced on basil leaves during drying was evaluated by scanning electron microscopy. From a sensory standpoint, fresh basil was described as having a fresh, herbaceous and floral odour, while the dried samples had a mentholated, spicy, hay‐like and earthy odour. Copyright © 2004 Society of Chemical Industry     

Microgenetic multiobjective reconfiguration algorithm considering power losses and reliability indices for medium voltage distribution network

This study proposes and applies an evolutionary-based approach for multiobjective reconfiguration in electrical power distribution networks. In this model, two types of indicators of power quality are minimised: (i) power system's losses and (ii) reliability indices. Four types of reliability indices are considered. A microgenetic algorithm ('GA) is used to handle the reconfiguration problem as a multiobjective optimisation problem with competing and non-commensurable objectives. In this context, experiments have been conducted on two standard test systems and a real network. Such problems characterise typical distribution systems taking into consideration several factors associated with the practical operation of medium voltage electrical power networks. The results show the ability of the proposed approach to generate well-distributed Pareto optimal solutions to the multiobjective reconfiguration problem. In the systems adopted for assessment purposes, our proposed approach was able to find the entire Pareto front. Furthermore, better performance indexes were found in comparison to the Pareto envelope-based selection algorithm 2 (PESA 2) technique, which is another well-known multiobjective evolutionary algorithm available in the specialised literature. From a practical point of view, the results established, in general, that a compact trade-off region exists between the power losses and the reliability indices. This means that the proposed approach can recommend to the decision maker a small set of possible solutions in order to select from them the most suitable radial topology.     

Automated Design of Combinational Logic Circuits Using the Ant System

This paper proposes an application of the Ant System (AS) to optimize combinational logic circuits at the gate level. A measure of quality improvement is defined in partially built circuits to compute the distances required by the AS, and those solutions that represent functional circuits with a minimum number of gates are considered as optimal. The proposed methodology is described together with some examples taken from the literature that illustrate the feasibility of the approach.