Sharif Digital Repository

We propose an approach for finding an optimal path in a flexible jobshop manufacturing system considering two criteria of time and cost. With rise in demands, advancement in technology, and increase in production capacity, the need for more shops persists. Therefore, a flexible jobshop system has more than one shop with the same duty. The difference among shops with the same duty is in their machines with various specifications. A network is configured in which the nodes are considered to be the shops with arcs representing the paths among the shops. An Automated Guided Vehicle (AGV) functions as a material handling device through the manufacturing network. To account for uncertainty, we... 

In this paper, we investigate an efficient deadlock-free shortest path routing algorithm for WK-recursive mesh networks which has been shown that possess several advantages like suitable to be manufactured by VLSI technology and easy to be expanded. It will be shown that the proposed algorithm requires O(√n) routing steps (where N is the network size) to route the entire network by exploiting either the self-routing or second order routing scheme. © Springer-Verlag Berlin Heidelberg 2008  

Traffic assignment is a step of travel demand estimation. Given a trip origin-destination demand matrix, this step determines traffic flow in each link, according to assumptions based on the behavior of drivers. Conventional assignment algorithms, which are mostly based on the Wardrop first principle of user equilibrium, assume that all drivers choose the shortest path to the destination, based on the same travel time computed by travel time functions. However, in reality, driver perception of travel time varies for a specific route. This paper presents a traffic assignment algorithm which assumes that driver perception of travel time affects route choices. Fuzzy set theory is used to define... 

We are concerned with the design of a model and an algorithm for computing the shortest path in a network having various types of fuzzy arc lengths. First, a new technique is devised for the addition of various fuzzy numbers in a path using α-cuts by proposing a least squares model to obtain membership functions for the considered additions. Due to the complexity of the addition of various fuzzy numbers for larger problems, a genetic algorithm is presented for finding the shortest path in the network. For this, we apply a recently proposed distance function for comparison of fuzzy numbers. Examples are worked out to illustrate the applicability of the proposed approach  

We consider biobjective shortest path problems in networks with fuzzy arc lengths. Considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the biobjective problems. The first and second approaches are extensions of the labeling method to solve the single objective problem and the third approach is based on dynamic programming. The labeling methods usually producing several nondominated paths, we propose a fuzzy number ranking method to determine a fuzzy shortest path. Illustrative examples are worked out to show the effectiveness of our algorithms  

This paper introduces the connection-graph-stability method and uses it to establish a new lower bound on the algebraic connectivity of graphs (the second smallest eigenvalue of the Laplacian matrix of the graph) that is sharper than the previously published bounds. The connection-graph-stability score for each edge is defined as the sum of the lengths of the shortest paths making use of that edge. We prove that the algebraic connectivity of the graph is bounded below by the size of the graph divided by the maximum connection-graph-stability score assigned to the edges  

The problem of finding the expected shortest path in stochastic networks, where the presence of each node is probabilistic and the arc lengths are random variables, have numerous applications, especially in communication networks. The problem being NP-hard we use an ant colony system (ACS) to propose a metaheuristic algorithm for finding the expected shortest path. A new local heuristic is formulated for the proposed algorithm to consider the probabilistic nodes. The arc lengths are randomly generated based on the arc length distribution functions. Examples are worked out to illustrate the applicability of the proposed approach  

This paper proposes a new approach to study the sensitivity analysis in the network flow problems, in particular, the minimum spanning tree and shortest path problems. In a sensitivity analysis, one looks for the amount of changes in the edges’ weights, number of edges or number of vertices such that the optimal solution, i.e., the minimum spanning tree or shortest path does not change. We introduce a novel approach, and develop associated equations and mathematics. We discuss two illustrative examples to show the applicability of the proposed approach. © International Journal of Industrial Engineering  

By applying shortest path analysis in stochastic networks, we introduce a new approach to obtain the reliability function of time-dependent systems. 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 that 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 stochastic network... 

In this paper, we study the problem of finding the shortest path in stochastic graphs and propose an iterative algorithm for solving it. This algorithm is based on distributed learning automata (DLA), and its objective is to use a DLA for finding the shortest path from the given source node to the given destination node whose weight is minimal in expected sense. At each stage of this algorithm, DLA specifies edges needed to be sampled. We show that the given algorithm finds the shortest path with minimum expected weight in stochastic graphs with high probability which can be close to unity as much as possible. We compare the given algorithm with some distributed learning automata-based... 

In this paper, we study the problem of finding the shortest path in stochastic graphs and propose an iterative algorithm for solving it. This algorithm is based on distributed learning automata (DLA), and its objective is to use a DLA for finding the shortest path from the given source node to the given destination node whose weight is minimal in expected sense. At each stage of this algorithm, DLA specifies edges needed to be sampled. We show that the given algorithm finds the shortest path with minimum expected weight in stochastic graphs with high probability which can be close to unity as much as possible. We compare the given algorithm with some distributed learning automata-based... 

In this paper, we study the problem of finding the shortest path in stochastic graphs and propose an iterative algorithm for solving it. This algorithm is based on distributed learning automata (DLA), and its objective is to use a DLA for finding the shortest path from the given source node to the given destination node whose weight is minimal in expected sense. At each stage of this algorithm, DLA specifies edges needed to be sampled. We show that the given algorithm finds the shortest path with minimum expected weight in stochastic graphs with high probability which can be close to unity as much as possible. We compare the given algorithm with some distributed learning automata-based... 

We propose an approach for finding an optimal path in a flexible jobshop manufacturing system considering two criteria of time and cost. With rise in demands, advancement in technology and increase in production capacity, the need for more shops persists. Therefore, a flexible jobshop system has more than one shop with the same duty. The difference among shops with the same duty is in their machines with various specifications. A network is configured in which the nodes are considered to be the shops with arcs representing the paths among the shops. An automated guided vehicle functions as a material handling device through the manufacturing network. To account for uncertainty, we consider... 

This paper studies an iterative stochastic algorithm for solving the stochastic shortest path problem. This algorithm, which uses a distributed learning automata, tries to find the shortest path by taking a sufficient number of samples from the edges of the graph. In this algorithm, which edges to be sampled are determined dynamically as the algorithm proceeds. At each iteration of this algorithm, a distributed learning automata used to determine which edges to be sampled. This sampling method, which uses distributed learning automata, reduces the number of samplings from those edges, which may not be along the shortest path, and resulting in a reduction in the number of the edges to be... 

We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α-cuts. Then, we propose a regression model for obtaining membership function for the considered addition. Finally, we present a dynamic programming method for finding a shortest path in the network. An example is worked out to illustrate the applicability of the proposed approach  

This paper proposes a method to solve shortest path problems in route choice processes when each link's travel time is a fuzzy number, called the Perceived Travel Time (PTT). The PTT is a subjective travel time perceived by a driver. The algorithm solves the fuzzy shortest path problem (FSPA) for drivers in the presence of uncertainty regarding route travel time. For congested networks, the method is able to find the shortest path in terms of perceived travel time and degree of saturation (congestion) along routes at the same time. The FSPA can be used to support the fuzzification of traffic assignment algorithms. The applicability of the resulting FSPA for the traffic assignment was tested... 

Implanted biomedical sensor networks provide a major application of sensor networks in the near future. Their high temperature due to wireless communication, might damage the surrounding tissues. This paper presents an efficient thermal-aware routing. Our proposed protocol states that when some nodes in the shortest path have a high temperature, ignores this path. The simulation results indicate the superiority of the proposed method compared to other thermal-aware routing protocols in terms of reducing temperature without a significant increase in packet delivery delay and power consumption of nodes. © 2009 IEEE  

We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α-cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers, we present a dynamic programming method for finding a shortest path in the network. Examples are worked out to illustrate the applicability of the proposed model  

The shortest path problem is a classical and important network optimization problem appearing in many applications. We discuss the shortest path problem from a specified vertex to every other vertex on a network with imprecise arc lengths as fuzzy numbers. Using an order relation between fuzzy numbers, we propose a new algorithm to deal with the fuzzy shortest path problem. The algorithm is composed of a fuzzy shortest path length procedure and a similarity measure. The fuzzy shortest length method is proposed to find the fuzzy shortest length, and the fuzzy similarity measure is utilized to get the shortest path. Two illustrative examples are worked out to demonstrate the proposed algorithm... 

In this paper, we consider acyclic networks of queues as a model to support the design of a dynamic production system. Each service station in the network represents a manufacturing or assembly operation. Only one type of product is produced by the system, but there exist several distinct production processes for manufacturing this product, each one corresponding with a directed path in the network of queues. In each network node, the number of servers in the corresponding service station is either one or infinity. The service time in each station is either exponentially distributed or belongs to a special class of Coxian distribution. Only in the source node, the service system may be...