Sharif Digital Repository

Although statistical modeling is a common task in different fields of science, it is still difficult to estimate the best model that can accurately describe inherent characteristics of a system for which historical or experimental data are available. Since we may classify estimating techniques as optimizations, we can model this problem as an optimization problem and solve it by a new heuristic algorithm like neural networks, genetic algorithms, and tabu search or by classic ones such as regression and econometric models. In this paper, we propose a new type of genetic algorithm to find the best regression model among all suggested and evaluate its performances by an economical case study. ©... 

In recent years, attention to blood supply chain in disaster circumstances has significantly increased. Disasters, especially earthquakes, have adverse consequences such as destruction, loss of human lives, and undermining the effectiveness of health services. This research considers a six-echelon blood supply chain which consists of donors, blood collection centers (permanent and temporary), regional blood centers, local blood centers, regional hospitals, and local hospitals. For the first time, we considered that helicopters could carry blood from regional hospitals to local hospitals and return injured people that cannot be treated in local hospitals to regional hospitals due to the... 

By applying shortest path analysis in stochastic networks, we introduce a new approach to obtain the reliability function of time-dependent systems with standby redundancy. We assume that not all elements of the system are set to function from the beginning. Upon the failure of each element of the active path in the reliability graph, the system switches to the next path. Then, the corresponding elements are activated and consequently the connection between the input and the output is established. It is also assumed each element exhibits a constant hazard rate and its lifetime is a random variable with exponential distribution. To evaluate the system reliability, we construct a directed... 

Although managing and controlling the inventories of perishable products is progressively becoming more important, they are often neglected in lot-sizing research and modeling. This paper studies a new multi-product multi-period dynamic lot sizing problem, where the inventories of products are assumed to be expired at a pre-specified date. For this purpose we assume a retailer that purchases products in large quantities (lot size) from manufacturers, and then sells smaller quantities (or single units) to the consumer. So, the order quantities can be merely an integer multiplier of that product batch size. The retailer also owns a capacitated warehouse. In order to make decisions on "how much... 

This study presents a new ray tracing acceleration technique for site-specific propagation modelling in indoor environments. It overcomes one of the major problems regarding the computational efficiency of shooting-and-bouncing-ray (SBR) method, that is most of the rays emitted from the source do not reach the receiver whereas all of them must be traced. Our proposed method solves this problem in a two-step procedure based on the idea of line search theory. In the first step, called the bracketing phase, the solid angles around the transmitter that transport electromagnetic power to the receiver are determined. In the second step, called the sectioning or zoom phase, the accuracy is improved... 

There is a unanimous agreement that "systems thinking" helps both individuals and organizations make more intelligent and more effective decisions. On the other hand, the unsatisfactory rate of systems thinking evolution among managers, collegians, students and other stratums raises this question that, why such a useful, discriminating and tasteful concept in theory, does not spread with the desirable pace in practice. Where exactly does the problem originate from? The tragedy is more sensible when noting the fact that even those who know the concept methodically do not apply it in action and in their decisions. Unfortunately, despite relatively numerous literatures on changing beliefs,... 

Distribution companies try to meet different goals such as increasing profitability, reducing investment and improving reliability indices. Therefore, distribution network planning has converted into complex multi-objective optimization problems. Mathematicians and operation research experts have developed many methods which can be used for solving these problems. Despite all efforts to develop applicable approaches for these problems, there is still no general consensus on project selection policy. Evaluating the strengths and weaknesses of each network optimization strategy selection in pragmatic manner is the objective of current research. In this paper, many methods used in network... 

In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a given multi-aspect task/project. Each task needs a diverse set of skills and the group of assigned experts should be able to collectively cover all required aspects of the task. We consider three types of multiaspect team formation problems and propose a unified framework to solve these problems accurately and efficiently. Our proposed framework is based on Facility Location Analysis (FLA) which is a well known branch of the Operation Research (OR). Our experiments on a real dataset show significant improvement in comparison with the state-of-the art approaches for the team formation... 

We consider coordination by contract in a divergent supply chain including one manufacturer and several retailers which produces fashion products with short sale seasons. The retailers cooperate with the manufacturer as sales agents; i.e., they work in the framework of revenue sharing contracts. Because of their proximity to the market, retailers can provide more accurate demand forecast for the manufacturer when he wants to decide on his capacity building (expansion), product assignment decision and market prices with regard to retailers stiff due date, different lead times and different price-dependent demand functions. To ensure abundant supply and increase their sales, the retailers have... 

Sports scheduling has become an important area of applied operations research in recent years, since satisfying fans and teams' requests and revenues of a sports league and TV networks may be affected by quality of the league schedule. While this type of scheduling problem can be solved by mathematical methods and exact solutions are accessible, it computationally leads to hard problems. The travelling tournament problem (TTP) is defined as minimising total travelling distance for all teams in a league. In this study, a new mathematical model for the TTP with the no-repeater constraint is presented. In addition, a very fast hybrid metaheuristic algorithm is proposed, which combines particle... 

Outpatient appointment scheduling problems have recently gained increasing attention. This paper provides a comprehensive review of recent analytical and numerical optimization studies that present decision-support tools for designing and planning outpatient appointment systems (OASs). A structure for organizing the recent literature according to various criteria is provided, including a framework that classifies decisions at the strategic, tactical, and operational levels. The OAS literature is evaluated from four perspectives: problem settings, environmental factors, modeling approaches, and solution methods. In addition, research gaps and areas of opportunity for future research are... 

The Adomian Decomposition Method is employed in the solution of the two dimensional laminar boundary layer of Falkner-Skan equation for wedge. This work aims at the solution of momentum equation in the case of accelerated flow and decelerated flow with separation. The Adomian Decomposition Method is provided an analytical solution in the form of an infinite power series. The effect of Adomian polynomials terms is considered on accuracy of the results. The velocity profiles in boundary layer are obtained. Results show a good accuracy compared to the exact solution. © 2007 Elsevier B.V. All rights reserved  

The one-dimensional cutting stock problem has many applications in industries and during the past few years has been one of the centers of attention among the researchers in the field of applied operations research. In this paper, a revised version of Ant Colony Optimization (ACO) technique is presented to solve this problem. This paper is a sequel to the previous ACO algorithm presented by the authors. In this algorithm, according to some probabilistic rules, artificial ants will select cutting patterns and generate a feasible solution. Computational results show the high efficiency and accuracy of the proposed algorithm for solving one- dimensional cutting stock problem. © International... 

In this paper we develop two models; the without shortages and the completely backlogging shortages with the price dependant demand rate under time value of money and inflation, finite time horizon and exponentially deterioration rate with the objective of maximizing the present worth of the total system profit. Using the dynamic programming method for each model, we are able to obtain different selling price, order quantity and cycle length for each cycle. We also use a proper numerical example to show accuracy of the solution procedures and to compare the results. This research and its results are unique and have never been concluded before  

In this paper, an analytical method is developed to compute the project completion time distribution in a dynamic PERT network, where the activity durations are exponentially distributed random variables. The projects are generated according to a renewal process and share the same facilities. Thus, these projects cannot be analyzed independently. The authors' approach is to transform this dynamic PERT network into a stochastic network and, then, to obtain the project completion time distribution by constructing a proper continuous-time Markov chain. This dynamic PERT network is represented as a network of queues, where the service times represent the durations of the corresponding activities... 

The mathematical techniques of decision making are among the most valuable outcomes of this research activity, which is generally referred to as realization in the operations, operational research or quantitative methods of decision making. Over time, with the increase in the complexity and the variety of decision making problems, the methods of decision making become more varied and will have more capability of problem solving. Multi-Criteria Decision Making (MCDM) is a collection of methodologies to compare, select, or rank multiple alternatives that involve incommensurate attributes. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is a multiple criteria... 

SnO2 is an important functional material having a wide range of applications in gas sensors and optoelectronic devices. There is a great interest for finding new cost-effective and straight-forward methods for production of these particles. In this research, hydrogel thermal decomposition method (HTDM) is used for production of high purity SnO2 nano-particles. Cost effective reactants and green routs of production are the advantages of polysaccharide based hydrogel as starting material for this method. Visual observations indicated that there is very little tendency for agglomeration in the SnO2 nano-particles produced by this method which can be considered as an advantage for this method... 

Transportation Network Design Problem (TNDP) aims at selection of a subset of proposed urban projects in budget constraint to minimize the network users' total travel time. This is a well-known resource-intensive problem in transportation planning literature. Application of parallel computing, as a result, can be useful to address the exact solution of TNDP. This paper is going to investigate how the performance of a parallel Branch-and-Bound (B&B) algorithm with Depth-First-Search (DFS) strategy can be accelerated. The paper suggests assigning greedy solutions to idle processors at the start of the algorithm. A greedy solution, considered in this paper, is a budget-wise feasible selection...