Sharif Digital Repository

Selection and development of machining features are the core activity in process planning. Usually the machining features development is done by experts according to elementary volumes. Performing this process by experts develops a limited machining features and the optimum solution may be missed. In this study a new method is developed to generate machining features and analyzes them to extract feasible features. The feasible solution is based on technical limitation of parts without any expert's judgments. Also it uses a set covering optimization technique to extract optimum one. Finally, the numerical results are presented and performance of the proposed method is tested by some candidate... 

In general coding theory, we often assume that error is observed in transferring or storing encoded symbols, while the process of encoding itself is error-free. Motivated by recent applications of coding theory, in this paper, we consider the case where the process of encoding is distributed and prone to error. We introduce the problem of distributed encoding, comprised of a set of K ∈ N isolated source nodes and N ∈ N encoding nodes. Each source node has one symbol from a finite field, which is sent to each of the encoding nodes. Each encoding node stores an encoded symbol from the same field, as a function of the received symbols. However, some of the source nodes are controlled by the... 

A novel, simple and rapid spectrophotometric method for the determination of nitrophenol (NP) isomer mixtures based on the catalytic activity of gold nanoparticles is described. Gold nanoparticle (∼13 nm) solution was used to catalyze the reduction of NP isomers to aminophenols with an excess amount of NaBH4. The second-order data were obtained by spectrophotometrically monitoring the reduction process of NP isomers. So, multivariate curve resolution optimized by alternative least squares (MCR-ALS) was used to analyze such data. MCR-ALS, an appropriate second-order method, can exploit the so-called 'second order advantage' (the ability to determine in the presence of uncalibrated... 

This paper presents an event-driven simulation-based optimization method for solving the train timetabling problem to minimize the total traveling time in the hybrid single and double track railway networks. The simulation approach is well applied for solving the train timetabling problems. In present simulation model, the stations and block sections of the railway network are respectively considered as the nodes and edges of the network model. The developed software named SIMARAIL has the capability of scheduling trains in large scale networks respecting the capacity constraints and infrastructure characteristics. This simulation model for railway timetabling is based on a detailed... 

The railroad blocking problem is an important issue at the tactical level of railroad freight transportation. This problem consists of determining paths between the origins and destinations of each shipment to minimize the operating and user costs while satisfying the railroad supply and demand restrictions. A mixed-integer program (MIP) is developed to find the optimal paths, and a new heuristic is developed to solve the proposed model. This heuristic decomposes the model into two sub-problems of manageable size and then provides feasible solutions. We discuss the performance of the proposed heuristic for a set of instances with up to 90 stations. A comparison with the CPLEX MIP solver... 

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... 

The vehicle routing problem (VRP) is one of the most complicated optimization mathematical models; the school bus routing problem (SBRP) is an important and practical branch of this problem. Because the number of variables and equations is vast, finding the exact solution for this problem under real conditions is difficult; only heuristic and metaheuristic algorithms can be used to solve it. Recently, the ejection chain method (ECM) has been introduced as a heuristic algorithm that efficiently finds a new neighbor solution. In a case study in developing countries, efficiency of several heuristic algorithms including ECM along with one metaheuristic algorithm-tabu search algorithm (TSA)-is... 

The traffic assignment problem (TAP) is traditionally defined without side constraints. Although introducing side constraints into the TAP is used as a way of refining applied assignment models, it brings some computational difficulties that prevent the refined model from being applicable in real-case problems. In this paper an iterative solution algorithm is developed for TAP with linear side constraints. This method is based on implicitly considering the side constraints by means of adding a dynamic penalty function (DPF) to the link travel times. Each of the iterations of the algorithm is reduced to an unconstrained assignment followed by updating the penalty functions. The unconstrained... 

Traffic assignment problem (TAP) is traditionally defined without side constraints. Although introducing the side constraints into the TAP is used as a way of refining the applied assignment models, it brings some computational difficulties preventing the refined model to be applicable in the real-case problems. In this paper an iterative solution algorithm is developed for TAP with linear side constraints. This method is based on implicitly considering the side constraints by means of adding a dynamic penalty function (DPF) to the link travel times. Each of the iterations of the algorithm is reduced to an unconstrained assignment followed by updating the penalty functions. The unconstraint... 

In the present contribution, a new approach based on mutual information (MI) is proposed for exploring the independence of feasible solutions in two component systems. Investigating how independent are different feasible solutions can be a way to bridge the gap between independent component analysis (ICA) and multivariate curve resolution (MCR) approaches and, to the best of our knowledge, has not been investigated before. For this purpose, different chromatographic and hyperspectral imaging (HSI) datasets were simulated, considering different noise levels and different degrees of overlap for two-component systems. Feasible solutions were then calculated by both grid search (GS) and...