Sharif Digital Repository

This paper presents a bi-objective vendor managed inventory (BOVMI) model for a supply chain problem with a single vendor and multiple retailers, in which the demand is fuzzy and the vendor manages the retailers' inventory in a central warehouse. The vendor confronts two constraints: number of orders and available budget. In this model, the fuzzy demand is formulated using trapezoidal fuzzy number (TrFN) where the centroid defuzzification method is employed to defuzzify fuzzy output functions. Minimizing both the total inventory cost and the warehouse space are the two objectives of the model. Since the proposed model is formulated into a bi-objective integer nonlinear programming (INLP)... 

This paper introduces a novel and practical integration of the inventory control and vendor selection problems for a manufacturing system that provides multiple products for several stores located in different places. The replenishment policy of each store is the economic order quantity under a multi-sourcing strategy in which the demand rate decreases as the selling price increases. In this strategy, the ordered quantity of each store for each product can be replenished by a set of selected vendors among all. In addition, the selected vendors can deliver the required products within a certain time window based on a soft time-window mechanism. The aim is to minimize the total system cost and... 

Accurate prediction of electricity demand is essential for planning, policy making and resource allocation in national level. In this manuscript, we applied a number of artificial intelligence methods to predict macro-scale electricity consumption rates in Iran. To this end, three socio-economic and three environmental factors were considered as inputs to the prediction models. We used data for the period 1967-2013 in order to predict the power demand in the years 2014-2018. Experimental results showed that the path coefficient analysis model with linear coefficients had the best performance among the models considered in this study. The outcome of this research can help the policy makers to... 

We propose modified hybridizations of genetic algorithms with some neighborhood search based metaheuristics. In our hybrid algorithms, we consider gradually increasing probability for the application of the neighborhood search procedure on the best individuals as the number of iterations of the genetic algorithm increases. We implement the proposed hybrid algorithms and compare their performance with two other recently proposed hybrid algorithms which, in contrast, use the neighborhood search procedure on all the individuals of the population, two hybrid algorithms applying simulated annealing on the best individual in the papulation in every iteration and three non-hybrid metaheuristic... 

The Stochastic Distribution Control (SDC) problem is a generalised form of the minimum variance control problem where non-Gaussian noise distributions are encountered. The problem has been previously solved using two alternative approaches. When it is assumed that the output Probability Distribution Function (PDF) is measurable, then a parameterized controller is obtained. If on the other hand this assumption is removed (which corresponds to most practical cases), then the controller found is no longer parameterisable (i.e. it is a control action sequence). Both these approaches have thus far been solved using local Newtonian methods. In this paper a third alternative is presented which... 

This paper proposes a new method based on Particle Swarm Optimization (PSO) for feature selection in phonemes sound classification. Inspired of biologist's studies, each particle is represented by filterbank which is motivated by human hearing. Thus, we propose a technique in which PSO is used to extract audio features similar to human's ear in order to achieve better classification. We use PSO technique for optimizing particle's filterbank in order to classify sound signals accurately. Then, feature extraction is done by using particle's information. Moreover, a classification method based on nearest neighbor is used. Furthermore, by using a defined fitness function in this paper, the... 

In this paper, an extension of the recently developed Crow Search Algorithm (CSA) to multi-objective optimization problems is presented. The proposed algorithm, called Multi-Objective Crow Search Algorithm (MOCSA), defines the fitness function using a set of determined weight vectors, employing the max-min strategy. In order to improve the efficiency of the search space, the performance space is regionalized using specific control points. A new chasing operator is also employed in order to improve the convergence process. Numerical results show that MOCSA is closely comparable to well-known multi-objective algorithms. © 2017 IEEE  

From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature power cycles for reduction in exergy destruction occurring during heat absorption/rejection processes due to their suitable boiling characteristics. In this study, comprehensive energetic and exergetic analyses are mathematically performed for an organic Rankine cycle (ORC) system employing a potential binary zeotropic working fluid, namely R717/water. For this purpose, initially mass, energy, and exergy balance equations are derived. With regard to the similarity in molar mass of R717 (17.03 g mol−1) and water (18.01 g mol−1), there is no need to alter the size of the... 

Three-dimensional analysis of combustion chambers in industrial gas turbines suffers from lack of simple and accurate reduced mechanisms for oxidation of hydrocarbon fuels. Here, an integrated procedure is introduced based on a differential evolution optimization technique. The procedure is flexible and modular and allows optimization of many rate parameters of a multistep global mechanism based on many different combustion criteria and inlet or operational conditions. The procedure uses any selected chemical reactor model and any reference combustion mechanism provided. Sample design criteria used here are flame temperature, ignition delay time, and concentration of selected species,... 

Recombination in Genetic Algorithms (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 by design. This paper presents a novel evolutionary approach based on symbiogenesis which uses symbiotic combination instead of sexual recombination, and by using this operator, it requires no domain knowledge for chromosome or combination operator design. The algorithm is benchmarked on three problem sets: combinatorial optimization category, deceptive problems, and fully deceptive... 

From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature power cycles for reduction in exergy destruction occurring during heat absorption/rejection processes due to their suitable boiling characteristics. In this study, comprehensive energetic and exergetic analyses are mathematically performed for an organic Rankine cycle (ORC) system employing a potential binary zeotropic working fluid, namely R717/water. For this purpose, initially mass, energy, and exergy balance equations are derived. With regard to the similarity in molar mass of R717 (17.03 g mol −1 ) and water (18.01 g mol −1 ), there is no need to alter the size of... 

This paper develops a new evolutionary algorithm for generating low autocorrelation binary sequences. These sequences are of interest in pulse compression technique. The proposed algorithm is fast enough to yield optimum or near optimum codes. The generated sequences were compared to the best literature and were seen that its results are better than the others. This suggested method could change 11 rows of the previous best known PSLs table, whereas the previous literature could change only one record. These records were combined with the best results reported in the papers to produce a new best minimal-PSL binary sequence table for bit lengths 71 through 100. ©2008 IEEE  

In the new environment of power system, generating units dispatch problem plays an important role inasmuch as it is used to clear power market transactions. That is, market operator solves an optimization problem in order to find the energy and capacity reserve quota of each generating units participating in the power market. There are different techniques for solving this problem which differ in many aspects, including the objective function, optimization algorithm, and feasibility, so using an efficient technique is vital. In the real competitive electricity market, the components of generating units dispatch problem are faced with the uncertainties; therefore, due to the presence of... 

The main contribution of this paper is utilizing bio-inspired evolutionary algorithm for reliability oriented high level synthesis. In this paper genetic algorithm is used to schedule a data-flow graph considering latency and resource allocation considering resource constraints and area overhead. Then a co-evolutionary strategy merges the results of these solutions to find the RT level design of the circuit which satisfies both performance and area constraints. To satisfy the user-defined reliability, another genetic algorithm is developed to insert some hardware redundancies to the resulted data-path. Experimental results show using the proposed approach results in an acceptable reliability... 

In this paper we have proposed an evolutionary algorithm to induct fuzzy classification rules. The algorithm uses an ant colony optimization based local searcher to improve the quality of final fuzzy classification system. The proposed algorithm is performed on Intrusion Detection as a high-dimensional classification problem. Results show that the implemented evolutionary ACO-Based algorithm is capable of producing a reliable fuzzy rule based classifier for intrusion detection. © 2007 IEEE  

In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and λ iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for convergence is considerably smaller compared to classical methods. © 2006 IEEE  

This paper represents the detailed results of an evolutionary optimization framework towards the exploration of vortex mechanisms leading to effective anti-vortex film cooling. In this regards, several arrangements of triple cooling holes were studied on flat and curved geometries using differential-evolution optimization algorithm and a modified Reynolds-stress based flow solver. Depending on the flow and geometric parameters, four distinct types of vortex interaction with different cooling mechanisms were identified. The vortex-trapping mechanism, observed in the optimized upstream arrangement acts through imposing a mild downwash over the main counter-rotating vortex pair and provides the... 

In this study, modeling of an irreversible thermoelectric heat pump was conducted, and its performance was assessed in terms of exergy for 10, 20, 30 and 40 K difference in temperature (∆T) by changing the values of the design parameters. By employing this model, positive impact of increasing cross-section area, current and thermocouple’s length which in turn increases the exergy efficiency is realized. In addition, diminishing adverse impact of adding more thermocouples on the exergy efficiency of the system is illustrated. Afterward, exergoeconomic performance of the thermoelectric heat pump is evaluated. Then, exergoeconomic factor for each of the system’s components is diagnosed. The... 

The wide range of wireless sensor network applications has made it an interesting subject for many studies. One area of research is the controlled node placement in which the location of nodes is not random but predetermined. Controlled node placement can be very effective when either the price of the sensor nodes is high or the sensor coverage is of a specific type and it is necessary to provide special characteristics such as coverage, lifetime, reliability, delay, efficiency or other performance aspects of a wireless sensor network by using the minimum number of nodes. Since node placement algorithms are NP-Hard problems, and characteristics of a network are often in conflict with each... 

This paper presents a multi-objective availability-redundancy allocation optimization model for a hyper-system. The hyper-system consists of B systems with shared resources. The structure of the systems is series-parallel subsystems consisting of multi-failure and multi-state components. The components may be purchased from different suppliers based on their price and discounts. It is assumed that technical and organizational activities continuously affect the components' failure rates and the subsystems' working conditions before starting the system's mission horizon. The model aims to find the optimal number and the type of the subsystems' components for all systems from each supplier and...