A Social Based Model For Genetic Algorithms.

Genetic algorithms (GAs), as a general search model, have proved its success in several applications, however, recently, several researchers have argued that they have slow convergence; this slowness is due to the randomness in all their operations. Therefore, recent researches have employed structured populations, in order to eliminate randomness, such as island models, cellular model, multinational evolutionary algorithms, etc. In this proposal, a social based GA is introduced; this model is trying to mimic the actual social behavior and the actual death and birth process. We will restrict the recombination for males to the only permitted females; we also divide the population into nearly separated subgroups (similar to the island model). Our motivation to such an approach is that we expect the nature to be more robust and optimal; hence the objectives of this work are to study the effects of these social rules and customs on the standard GA, and to investigate its effects on the speed of convergence of GA. The results will be analyzed according to parameters that depend on the social behavior and the natural birth and death models

Adopting AHP in evaluating nurse scheduling methods

When comparing and evaluating two or more scheduling methods the need to use a multiple criteria decision making technique arises.Instead of just employing a qualitative approach of evaluating the methods, one can integrate the qualitative and the quantitative data in the evaluation process through the use of the analytic hierarchy process (AHP).Hence, this paper reports the evaluation of two nurse scheduling methods where the AHP technique is employed to support the selection process of these methods.Five decision criteria are used in the process.The main objective of the scheduling methods (models) is to assign work shifts and off days of the nurses in a particular hospital unit such that, it fulfils certain specified constraints while ensuring continuous high-quality patient care services.The first method is a heuristic procedure that is currently in practice.The other one is a prototype in which a memetic algorithm is adopted in the approach.The application of AHP has been found to provide a better transparency of the capability and efficiency of the scheduling methods. Consequently, the memetic algorithm approach stands out to be the better one based on the evaluation scheme

An Adaptive GA in Partitioned Search Space

Evolutionary algorithms are population based meta-heuristics inspired from natural survival of fittest phenomena.Despite their reasonable performance, these algorithms suffer from some weaknesses including the need for finding the values of their parameters that affect their performance.A new algorithm is proposed that divide the search space into equal sized partitions.Each partition is assigned with two parameters that determine the intensification and diversification rates.The partitions will be intensified or diversified adaptively with regards to the corresponding parameters.Traditional crossover and mutation operators are replaced with two new parameter-free operators.The experiments conducted on a wide range of multi-modal and epistatic problems showed the superiority of the proposed method in comparison to other algorithms in literature

Data Pre Processing Methodology for Computational Experiment in Analyzing Protein Interaction Networks

The aim of this process flow is to fulfill the requirement oj our graph-based algorithm's solution and to ensure that the representation of protein interaction network which consist ofnodes and edges are accurate

Comparison Of HSRNAFold and RNAFold Algorithms for RNA Secondary Structure Prediction.

Ribonucleic Acid (RNA) has important structural and functional roles in the cell and plays roles in many stages of protein synthesis. The structure of RNA largely determines its function

A Classification And Visualization Approach For Knowledge Management Of A Special Interest Group

Some Web portals are developed to support electronic community or e-community of special interest groups (SIG) that provide the platforms to communicate, share ideas and knowledge among the members. By incorporating the Web portal with a knowledge-based system, knowledge acquisition and sharing will be more efficient

Evaluating the Location Efficiency of Arabian and African Seaports Using Data Envelopment Analysis (DEA)

In this paper the efficiency and performance is evaluated for 22 seaports in the region of East Africa and the Middle East. The aim of our study is to compare seaports situated on the maritime trade road between the East and the West. These are considered as middledistance ports at which goods from Europe and Far East/Australia can be exchanged and transhipped to all countries in the Middle East and East Africa. All these seaports are regional coasters, and dhow trade was built on these locations, leading this part of the world to become an important trade centre. Data was collected for 6 years (2000-2005) and a non-parametric linear programming method, DEA (Data Envelopment Analysis) is applied. The ultimate goal of our study is: 1) to estimate the performance levels of the ports under consideration. This will help in proposing solutions for better performance and developing future plans. 2) to select optimum transhipment locations.Middle East and East African Seaports; Data Envelopment Analysis; Seaports Efficiency; Performance measurement of Containers Ports; transshipment.

Cellular automata model for pedestrian evacuation in fire spreading conditions

In this paper, a two-dimensional cellular automata model presented to simulate pedestrians evacuation in fire spreading conditions.In this proposed model, the movement of pedestrians is represented as “chaotic”, mimicking panic egress behaviors during a fire evacuation.This model includes a fire circular front shape based on the spiral movement technique. Simulation results show that this model can be used to predict the number of pedestrians who have evacuated safely or have been killed

A harmony search algorithm for university course timetabli

One of the main challenges for university administration is building a timetable for course sessions. This is not just about building a timetable that works, but building one that is as good as possible. In general, course timetabling is the process of assigning given courses to given rooms and timeslots under specific constraints. Harmony search algorithm is a new metaheuristic population-based algorithm, mimicking the musical improvisation process where a group of musicians play the pitches of their musical instruments together seeking a pleasing harmony. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. In this paper, a harmony search and a modified harmony search algorithm are applied to university course timetabling against standard benchmarks. The results show that the proposed methods are capable of providing viable solutions in comparison to previous works

A Hybrid Method Based on Cuckoo Search Algorithm for Global Optimization Problems

Cuckoo search algorithm is considered one of the promising metaheuristic algorithms applied to solve numerous problems in different fields. However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimization algorithm, which is a combination of Cuckoo search algorithm and Hill climbing called CSAHC discovers many local optimum traps by using local and global searches, although the local search method is trapped at the local minimum point. In other words, CSAHC has the ability to balance between the global exploration of the CSA and the deep exploitation of the HC method. The validation of the performance is determined by applying 13 benchmarks. The results of experimental simulations prove the improvement in the efficiency and the effect of the cooperation strategy and the promising of CSAHC