Sharif Digital Repository

In this paper, we apply the stochastic dynamic programming to find the dynamic shortest path from the source node to the sink node in stochastic dynamic networks, in which the arc lengths are independent random variables with exponential distributions. In each node there is an environmental variable, which evolves in accordance with a continuous time Markov process. The parameter of the exponential distribution of the transition time of each arc is also a function of the state of the environmental variable of its initiative node. Upon arriving at each node, we can move toward the sink node through the best outgoing arc or wait. At the beginning, it is assumed that upon arriving at each node,... 

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  

Existing revenue management methods and heuristics rely on specific demand-side assumptions such as customers' independent decisions over time. We relax the assumption that purchasing decisions depend only on the current price and are independent of previous prices of the same or similar products. On the contrary, we assume that customers' decisions depend on the product's past prices through a reference price. With this new dimension, a firm needs not only to manage its remaining capacity but also to control the reference price to maximize its expected future profit. In this situation, we show that some of the main analytical properties such as monotonicity or modularity of the firm's value... 

The lazy bureaucrat scheduling is a new class of scheduling problems that was introduced in [1]. In these problems, there is one employee (or more) who should perform the assigned jobs. The objective of the employee is to minimize the amount of work he performs and to be as inefficient as possible. He is subject to a constraint, however, that he should be busy when there is some work to do. In this paper, we focus on the cases of this problem where all jobs have the same common deadline. We show that with this constraint, the problem is still NP-hard, and prove some hardness results. We then present a tight 2-approximation algorithm for this problem under one of the defined objective... 

In conventional arrays, improving angular resolution requires larger aperture which demands more number of elements. On the other hand, array thinning is an efficient method of achieving narrow beamwidth (high angular resolution) with fewer number of elements. Reducing the number of elements results in reducing weight, cost, hardware complexity, and energy consumption. In this paper, a novel dynamic programming algorithm of array thinning with the objective of reducing sidelobe levels (SLLs), desired for large circular arrays, is proposed. The circular array is partitioned into annular rings, and the objective of the optimization problem is to determine the number of active elements in each... 

In order to design a decision-making framework in production environments, in this study, we use both the stochastic dynamic programming and Bayesian inference concepts. Using the posterior probability of the production process to be in state λ (the hazard rate of defective products), first we formulate the problem into a stochastic dynamic programming model. Next, we derive some properties for the optimal value of the objective function. Then, we propose a solution algorithm. At the end, the applications and the performances of the proposed methodology are demonstrated by two numerical examples. © 2007 Asian Network for Scientific Information  

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  

Revenue management (RM) and customer relationship management (CRM) are the standard strategies of many hotels to increase their profitability. Although the objectives and time horizons of RM and CRM are different, they can be considered as complimentary business strategies. However, the integration has received little attention both practically and theoretically. In this study, we develop an approach to jointly make the capacity allocation and overbooking decisions considering CRM strategies over a hotel network. Hotel customers are divided based on their lifetime value into two major groups of occasional and loyal customers. Price discounts and room availability guarantee (RAG) are offered... 

In this paper, we use both stochastic dynamic programming and Bayesian inference concepts to design an optimum-acceptance-sampling-plan policy in quality control environments. To determine the optimum policy, we employ a combination of costs and risk functions in the objective function. Unlike previous studies, accepting or rejecting a batch are directly included in the action space of the proposed dynamic programming model. Using the posterior probability of the batch being in state p (the probability of non-conforming products), first, we formulate the problem into a stochastic dynamic programming model. Then, we derive some properties for the optimal value of the objective function, which... 

Power management strategies play a key role in the design process of hybrid electric vehicles. Electric Assist Control Strategy (EACS) is one of the popular power management strategies for hybrid electric vehicles (HEVs). The present investigation proposes a new framework to advance the EACS. Dynamic Programming method is applied to an HEV model in several drive cycles, and as a result, some optimal operating regions are found. The obtained regions are almost distinct, and consequently, some threshold lines can be defined to separate them. The obtained threshold lines are used to eliminate some parameters of the EACS to reduce its sensitivity to the driving behavior. It is shown that by... 

If at least one out of two serial machines that produce a specific product in manufacturing environments malfunctions, there will be non conforming items produced. Determining the optimal time of the machines' maintenance is the one of major concerns. While a convenient common practice for this kind of problem is to fit a single probability distribution to the combined defect data, it does not adequately capture the fact that there are two different underlying causes of failures. A better approach is to view the defects as arising from a mixture population: one due to the first machine failures and the other due to the second one. In this article, a mixture model along with both Bayesian... 

Linear segmentation of a meeting conversation is beneficial as a stand-alone system (to organize a meeting and make it easier to access) or as a preprocessing step for many other meeting related tasks. Such segmentation can be done according to two different criteria: topic in which a meeting is segmented according to the different items in its agenda, and function in which the segmentation is done according to the meeting's different events (like discussion, monologue). In this article we concentrate on the function segmentation task and propose new unsupervised methods to segment a meeting into functionally coherent parts. The first proposed method assigns a score to each possible boundary... 

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  

In this paper, a simple memory limited transmitter for molecular communication is proposed, in which information is encoded in the emission rate of the molecules. Taking advantage of memory, the proposed transmitter reduces the ISI problem by properly adjusting its emission rate, which can be interpreted as water-filling on the expected interference. The error probability of the proposed scheme is derived and the result is compared with the error probability of the optimal transmitter obtained by dynamic programming methods. Furthermore, for the special case of channel with one symbol memory, a tight lower bound on error probability is derived. Numerical results show that the performance of... 

This paper presents a stochastic framework to properly involve the uncertainties associated with demand in distribution system restoration (DSR) problem. To reach this goal, these uncertainties are represented as probabilistic scenarios corresponding to different load levels. Subsequently, the associated stochastic optimization problem is formulated such that it can be readily solved using dynamic programming approach. Moreover, a clustering technique is presented that enables the dynamic programming approach to find near-optimal solutions for the stochastic load restoration problem with reasonable computational effort. The proposed framework is implemented on a real-world test system, and... 

In this research, we employ Bayesian inference and stochastic dynamic programming approaches to select the binomial population with the largest probability of success from n independent Bernoulli populations based upon the sample information. To do this, we first define a probability measure called belief for the event of selecting the best population. Second, we explain the way to model the selection problem using Bayesian inference. Third, we clarify the model by which we improve the beliefs and prove that it converges to select the best population. In this iterative approach, we update the beliefs by taking new observations on the populations under study. This is performed using Bayesian... 

In this paper, a dynamic-programming approach to the coupled translational and rotational control of thruster-driven spacecraft is studied. To reduce the complexity of the problem, dynamic-programming-based optimal policies are calculated using decoupled position and attitude dynamics with generalized forces and torques as controls. A quadratic-programming-based control allocation is then used to map the controls to actuator commands. To control the spacecraft in the event of thruster failure, both the dynamic programming policies and control allocation are reconfigured to cope with the losses in controls. The control allocation parameters are adjusted dynamically to ensure the satellite... 

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