Sharif Digital Repository

Natural earthquake disasters are unprecedented incidents which take many lives as a consequence and cause major damages to lifeline infrastructures. Various agencies in a country are responsible for reducing such adverse impacts within specific budgets. These responsibilities range from before to after the incident, targeting one of the main phases of disaster management (mitigation, preparedness, and response). Use of OR in disaster management and coordination of its phases has been mostly ignored and highly recommended in former reviews. This paper presents a formulation to coordinate three main agencies and proposes a heuristic approach to solve the different introduced sub-problems. The... 

A new algorithm named random particle optimization algorithm (RPOA) for local path planning problem of mobile robots in dynamic and unknown environments is proposed. The new algorithm inspired from bacterial foraging technique is based on particles which are randomly distributed around a robot. These particles search the optimal path toward the target position while avoiding the moving obstacles by getting help from the robot's sensors. The criterion of optimal path selection relies on the particles distance to target and Gaussian cost function assign to detected obstacles. Then, a high level decision making strategy will decide to select best mobile robot path among the proceeded particles,... 

In this paper, we combine a novel Sequential Graph Coloring Heuristic Algorithm (SGCHA) with a non-systematic method based on a cultural algorithm to solve the graph coloring problem (GCP). The GCP involves finding the minimum number of colors for coloring the graph vertices such that adjacent vertices have distinct colors. In our solving approach, we first use an estimator which is implemented with SGCHA to predict the minimum colors. Then, in the non-systematic part which has been designed using cultural algorithms, we improve the prediction. Various components of the cultural algorithm have been implemented to solve the GCP with a self adaptive behavior in an efficient manner. As a result... 

Enforced hill climbing (EHC), a heuristicaa search method, has been frequently used in a number of AI planning systems. This paper presents a new form of EHC, guided enforced hill climbing (GEHC), to enhance EHC efficiency. Main feature in GEHC is an adaptive ordering function. GEHC has shown a significant improvement in EHC efficiency, especially when applied to larger problems  

In this paper a method for enhancing the synchronizability of dynamical networks is discussed. The method considers both local structural properties, i.e. node degrees, and global properties, i.e. node and edge betweenness centrality measures. Its performance is compared with that of some other heuristic methods and the evidence for its superior behavior is discussed. As an index for the synchronizability of a dynamical network, the eigenratio of the Laplacian matrix of the connection graph is considered. As network structures, scale-free, Watts- Strogatz and random networks of different sizes and topological properties are used. Numerical calculations of the eigenratio in the networks... 

In recently proposed cipher algorithms, power functions over finite fields and specially inversion functions play an important role in the S-box design structure. In this study, a new systematic efficient method is introduced to cryptanalyse (to simplify and approximate) such S-boxes. This method is very simple and does not need any heuristic attempt and can be considered as a quick criterion to find some simple approximations. Using this new method, some approximations can be obtained for advanced encryption standard (AES) like S-boxes, such as AES, Camellia, Shark and so on. Finally as an application of this method, a simple linear approximation for AES S-box is presented. © The... 

In this paper we claim that local optimization can produce proper start point for genetic search. We completely test this claim on partitioning problem and on the performance of genetic search in a real problem that is finding aggregation tree in the sensor networks. The presented method (named Tendency algorithm) increases the performance of heuristic searches, and can be used in parallel with other tuning methods. The paper justifies the logic behind tendency algorithm by measuring the "entropy" of solution (in regard to optimal solution), and by numerous empirical tests. © 2008 IEEE  

Recently, there has been great interest in Bio informatics among researches from various disciplines such as computer science, mathematics, statistics and artificial intelligence. Bioinformatics mainly deals with solving biological problems at molecular levels. One of the classic problems of bioinformatics which has gain a lot attention lately is Haplotyping, the goal of which is categorizing SNP-fragments into two clusters and deducing a haplotype for each. Since the problem is proved to be NP-hard, several computational and heuristic methods have addressed the problem seeking feasible answers. In this work it is shown that using PCM to solve Haplotyping problem in DALY dataset yields... 

Harmony search (HS) is a new meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments' pitches searching for a perfect state of harmony. A new variant of HS, called global-best harmony search (GHS), is proposed in this paper where concepts from swarm intelligence are borrowed to enhance the performance of HS. The performance of the GHS is investigated and compared with HS and a recently developed variation of HS. The experiments conducted show that the GHS generally outperformed the other approaches when applied to ten benchmark problems. The effect of noise on the performance of the three HS variants is investigated and a... 

Procurement of optimum available transfer capability (ATC) in the restructured electricity industry is a crucial challenge with regards to open access to transmission network. This paper presents an approach to determine the optimum location and optimum capacity of TCSC in order to improve ATC as well as voltage profile. Real genetic algorithm (RGA) associated with analytical hierarchy process (AHP) and fuzzy sets are implemented as a hybrid heuristic technique in this paper to optimize such a complicated problem. The effectiveness of the proposed methodology is examined through different case studies. © 2007 Elsevier B.V. All rights reserved  

This paper develops an Improved harmony search (IHS) algorithm for solving optimization problems. IHS employs a novel method for generating new solution vectors that enhances accuracy and convergence rate of harmony search (HS) algorithm. In this paper the impacts of constant parameters on harmony search algorithm are discussed and a strategy for tuning these parameters is presented. The IHS algorithm has been successfully applied to various benchmarking and standard engineering optimization problems. Numerical results reveal that the proposed algorithm can find better solutions when compared to HS and other heuristic or deterministic methods and is a powerful search algorithm for various... 

Most positions of the human genome are typically invariant (99%) and only some positions (1%) are commonly variant which are associated with complex genetic diseases. Haplotype reconstruction is to divide aligned SNP fragments, which is the most frequent form of difference to address genetic diseases, into two classes, and thus inferring a pair of haplotypes from them. Minimum error correction (MEC) is an important model for this problem but only effective when the error rate of the fragments is low. MEC/GI as an extension to MEC employs the related genotype information besides the SNP fragments and so results in a more accurate inference. The haplotyping problem, due to its NP-hardness, may... 

In this paper, a new algorithm for solving the shortest loop design problem is presented. The shortest loop design problem is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. In this paper, first it is shown that this problem can be represented as a graph model. The properties of the presented model enable us to design a meta-heuristic based on ant colony system algorithm for solving the shortest loop design problem. Computational results show the efficiency of our algorithm in compare to the other techniques. © 2006 Elsevier Ltd. All rights reserved  

In this paper real-time optimization of the Tennessee Eastman challenge process is accomplished in a fuzzy environment. This study focuses on violation of TE constraints in fuzzy environment and also violation of some additional constraints originated from operating mode of the plant. Furthermore the objective function is treated in fuzzy form. Results show a great reduction of operating cost, which is selected as the objective function of this study. The theory of fuzzy optimization, which is the main contribution of this paper, is to reformulate the fuzzy constraints and fuzzy objective function into a crisp programming problem and to solve it by a conventional method of optimization. The... 

Sensor network deployment is very challenging due to hostile and unpredictable nature of usage environments. In this letter, we propose two methods for the self-deployment of mobile sensors. The first one is a randomized solution that provides both simplicity and applicability to different environments. Inspired by simulated annealing, it improves both speed and energy conservation of the deployment process. The other method is suggested for environments where sensors form a connected graph, initially. At the cost of this extra limitation, we gain considerable improvements. © 2006 IEEE  

In this paper, a genetic algorithm for solving a class of project scheduling problems, called Resource Investment Problems, is presented. Tardiness of the project is permitted with a defined penalty. The decision variables are the level of resources and the start times of the activities. The objective is to minimize the sum of resources and delay penalty costs, subject to the activities' precedence relations and some other constraints. A revised form of the Akpan heuristic method for this problem is used to find better chromosomes. Elements of the algorithm, such as chromosome structure, unfitness function, crossover, mutation, immigration and local search operations, are explained. The... 

In peer-to-peer (P2P) overlay networks, the mechanism of a peer randomly joining and leaving a network, causes a topology mismatch between the overlay and the underlying physical topology. This causes a large volume of redundant traffic in the underlying physical network as well as an extra delay in message delivery in the overlay network. Topology mismatch occurs because overlay networks are not aware of their underlying physical networks. In this paper we present a mathematical model for topology awareness of overlay networks (degree of matching between an overlay and its underlying physical network) and the efficiency of message delivery on them. We also after determining the... 

A resource investment problem is a project-scheduling problem in which the availability levels of the resources are considered as decision variables and the goal is to find a schedule, and resource requirement levels, such that some objective function optimizes. In this paper, we consider a resource investment problem in which the goal is to maximize the net present value of the project cash flows. We call this problem as Resource Investment Problem with Discounted Cash Flows (RIPDCF) and we develop a heuristic method to solve it. Results of several numerical examples show that the proposed method performs relatively well  

A new generation of sustainable development research uses mathematical models. This article proposes a heuristic approach to analyze sustainability in a society utilizing a mathematical model. First, an alternative definition of sustainable development has been proposed. Second, the interactions between transport and the other major components of a society have been simulated by a system of differential equations in the form of Lotka-Volterra type predator-prey model. Some of the model parameters have been considered as control parameters in order to reflect the impact of strategies of reducing transport and economic levels of activities in favour of the environment on the one hand, and... 

Existing load balancing solutions rely on direct or indirect measurement of rates (or congestion) averaged over short periods of time. Sudden fluctuations in flow rates can lead to significant undershooting/overshooting of target link loads. In this paper, we make the case for taking variations and correlations of flows into account in load balancing. We propose correlation-aware flow consolidation, i.e. aggregating inversely correlated (or uncorrelated) flows into superflows and using them as building blocks for load balancing. Superflows are smoother than individual flows, and thus are easier to estimate with a higher confidence, and can reduce overshooting/undershooting of link...