جستجوی مقالات مرتبط با کلیدواژه "graph theory" در نشریات گروه "صنایع"

Today, the electricity power system is the most complicated engineering system has ever been made. The integrated power generating stations with power transmission lines has created a network, called complex power network. The reliability estimation of such complex power networks is a very challenging problem, as one cannot find any immediate solution methods in current literature. In this paper, we advanced a new method for estimating the reliability of such networks, which is based on 1) decomposition of the whole network into sub-networks called islands, 2) estimating each island’s reliability in exact form using the network reliability theory, and 3) assembling the islands back together to estimate the whole network reliability, again in exact form. We applied the new method on Iran’s power network with 105 generation stations and 16460 kilometres of transmission lines.

Today, the electricity power system is the most complicated engineering system has ever been made. The integrated power generating stations with power transmission lines has created a network, called complex power network. The reliability estimation of such complex power networks is a very challenging problem, as one cannot find any immediate solution methods in current literature. In this paper, we advanced a new method for estimating the reliability of such networks, which is based on 1) decomposition of the whole network into sub-networks called islands, 2) estimating each island’s reliability in exact form using the network reliability theory, and 3) assembling the islands back together to estimate the whole network reliability, again in exact form. We applied the new method on Iran’s power network with 105 generation stations and 16460 kilometres of transmission lines.

Nurse Rostering Problem (NRP) or the Nurse Scheduling Problem (NSP) is a complex scheduling problem that affects hospital personnel on a daily basis all over the world and is known to be NP-hard.The problem is to decide which members of a team of nurses should be on duty at any time, during a rostering period of, typically, one month.It is very important to efficiently utilize time and effort, to evenly balance the workload among people and to attempt to satisfy personnel preferences.With demand ever fluctuating, designing a timetable to definea work schedule for each nurse is not an easy task.A NRP deals with a very high number of constraints.A lot of big healthcare organizations around the world still construct nurses’ duty roster manually.Many optimization algorithms have been proposedto solve NRPs such as exact algorithms and (Meta)heuristic algorithms. In this paper we propose an approach that use the graph theory concept to solve the problem. We use the graph coloring and bipartite graph concept. In our approach we first formulize the problem and solve it with exact algorithm and then by using the graph concept, the solution is improved. Finally by results obtained from the graph approaches the final timetable is available.In in order to validate the proposed approach some problems with different scales are solved. We solved the problems for 30, 40, 45 and 50 nurses. In all problems the proposed approach is efficient and for instance the relationship between the nurses are presented.

Many hierarchical techniques to solve large Markov decision processes (MDPs) are based on the partition of the state space into strongly connected components (SCCs) that can be classified into some levels. In each level, smaller problems named restricted MDPs are solved, and then these partial solutions are combined to obtain the global solution. In this paper, we first propose a novel algorithm, which is a variant of Tarjan’s algorithm that simultaneously finds the SCCs and their belonging levels. Second, a new definition of the restricted MDPs is presented to ameliorate some hierarchical solutions in discounted MDPs using value iteration (VI) algorithm based on a list of state-action successors. Finally, a robotic motion-planning example and the experiment results are presented to illustrate the benefit of the proposed decomposition algorithms.

Considering the major change occurred in business cells from plant to “chain” and the critical need to choose the best partners to form the supply chain for competing in today’s business setting, one of the vital decisions made at the early steps of constructing a business is supplier selection. Given the fact that the early decisions are inherently strategic and therefore hard and costly to change, it’s been a point of consideration for industries to select the right supplier. It’s clear that different criteria must be investigated and interfered in deciding on the best partner(s) among the alternatives. Thereupon the problem might be regarded as a multiple criteria decision making (MCDM) problem. There are a variety of techniques to solve a MCDM problem. In this paper we propose a novel technique by combination of decision making trial and evaluation laboratory and graph theory and matrix approach techniques. Eventually, the results are compared to SAW technique and discussed to come to a conclusion.