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Time, cost and quality are among the crucial aspects of each project. In recent years, the demands of project stakeholders regarding reductions in the total cost and time of a project along with achieving the acceptable quality of the project have risen significantly. This leads researchers to developing models that incorporate the quality factor to previously existing time cost trade-off models.We develop a model for discrete time-cost-quality trade-off problem. For each activity, an execution mode can be selected from a number of possible ones. The time and cost of each mode are assumed to be crisp but the quality of each mode is a linguistic variable. Therefore, in this paper, fuzzy logic... 

Introduction: The study of life and the detection of gene functions is an important issue in biological science. Multiple sequences alignment methods measure the similarity of DNA sequences. Nonetheless, when the size of genome sequences is increased, we encounter with the lack of memory and increasing the run time. Therefore, a fast method with a suitable accuracy for genome alignment has a significant impact on the analysis of long sequences. Methods: We introduce a new method in which, it first divides each sequence into short sequences. Then, it uses evolutionary algorithms to align the sequences. Results: The proposed method has been evaluated in seven datasets with different number of... 

Nature has always been a source of great inspiration for engineers and mathematicians. Evolutionary Algorithms are the latest in a line of natural-based innovations which have had a profound effect on the application of optimization in science and engineering. Although based on nature, Evolutionary Algorithms are nonetheless distinctly different from natural evolution in several areas. This paper outlines early and recent developments of Evolutionary Algorithms while covering those areas of difference. Practical issues related to the use of Evolutionary Algorithms, key parameters that affect the quality of the search and impact of user choices in problem formulation are also covered in this... 

Recent advances in wireless sensor network (WSN) technology are enabling the deployment of large-scale and collaborative sensor networks. WSNs face several challenges such as security, localisation, and energy consumption. To resolve these issues, evolutionary algorithms can be helpful. The core of every evolutionary algorithm is its fitness function. The drawbacks of fitness functions used in the literature will be investigated and some solutions will be suggested. The simulation results clearly show the improvement due to suggested solutions. © The Institution of Engineering and Technology 2017  

Recombination in the Genetic Algorithm (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations hopefully producing an offspring that has the good characteristics of both parents and this requires explicit chromosome and recombination operator design. This paper presents a novel evolutionary approach based on symbiogenesis which uses symbiotic combination instead of sexual recombination and using this operator, it requires no domain knowledge for chromosome or combination operator design. The algorithm is benchmarked on three problem sets, combinatorial optimization, deceptive, and fully deceptive, and is compared with standard... 

Decision models are essential tools for coastal groundwater management (CGM). A combined simulation-optimization framework is employed to develop these models. One of the main barriers in the widespread application of these models for real-world cases is their large computational burden. Recent advances in efficient computational approaches and robust optimization methods can crack this barrier. This study surveys the scientific basis of CGM to provide an overview on this subject and reviews the-state-of-the-art to clarify recent developments and to outline ideas for improving the computational performance. Key details are presented on the performance and choice of possible robust tools such... 

Due to the various contents of images, the stego images produced by a steganography method may have different levels of undetectability against steganalyzers. In other words, a steganography method may cause less detectable statistical artifacts on some images compared to other images. In this paper, we analyze different features of images to find the similarity between proper cover images for each steganography method Similarity between images is modeled in form of fuzzy if-then rules using an evolutionary algorithm. Subsequently for hiding secret data in a cover image, we suggest a reliable steganography method that results in an undetectable stego image against most recently reported... 

Using a proposed evolutionary algorithm, we have solved the inverse problem of finding the incident field on a high-aperture lens for generating a desired focused field, for the first time (to our knowledge). Further, we have achieved the global solution to the problem using this novel algorithm  

This paper presents a novel hybrid approach for intrusion detection in computer networks. The proposed approach combines an evolutionary based fuzzy system with an artificial immune system to generate high quality fuzzy classification rules. The performance of final fuzzy classification system has been investigated using the KDD-Cup99 benchmark dataset. The results indicate that in comparison to several traditional techniques, such as C4.5, Naïve Bayes, k-NN and SVM, the proposed hybrid approach achieves better classification accuracies for most of the classes of the intrusion detection classification problem. Therefore, the resulted fuzzy classification rules can be used to produce a... 

This paper presents a new approach to economic dispatch (ED) problem with non-continuous and non-smooth cost functions using a hybrid evolutionary programming (EP) algorithm. In the proposed method the concept of multi-agent (MA) systems and EP are integrated together to form a new multi-agent evolutionary programming (MAEP) approach. In MAEP, an agent represents a candidate solution to the optimization problem in hand, and all agents live together in a global environment. Each agent senses its local environment, competes with its neighbors, and also learns by using its own knowledge. MAEP uses these agent-agent interactions and the evolutionary mechanism of EP to obtain the optimal... 

The objective of the research done in this paper was to determine cost of the power and heat system with pressurized fluidized bed gasifier using exergoexonomic appraisal techniques. Exergetic efficiency maximization was approached with use of multi-objective evolutionary optimization methods which were designed such that the costs were minimized in line with the exergoeconomic plans. The results of this method were also compared to methods that employ iterative techniques. Results showed an almost 12.28% improvement in exergetic efficient that the system could reach through utilization of the multi-objective evolutionary algorithm  

A novel combination of a multimode project scheduling problem with material ordering, in which material procurements are exposed to the total quantity discount policy is investigated in this paper. The study aims at finding an optimal Pareto frontier for a triple objective model derived for the problem. While the first objective minimizes the makespan of the project, the second objective maximizes the robustness of the project schedule and finally the third objective minimizes the total costs pertaining to renewable and nonrenewable resources involved in a project. Four well-known multi-objective evolutionary algorithms including non-dominated sorting genetic algorithm II (NSGAII), strength... 

Ease of use, high flexibility and variety of applications have made wireless sensor networks very popular. Node placement in a sensor network is very critical since it affects important network attributes such as coverage, lifetime, and reliability. Therefore, controlled node placement is necessary for achieving specific network features with minimum number of nodes. Since node placement is an NP-hard problem, many placement algorithms have been proposed based on heuristic and meta-heuristic methods. Most of those algorithms assume a uniform event pattern (UEP) throughout the area under investigation. However, in practice some networks deal with non-uniform event pattern (NEP). Optimization...