Sharif Digital Repository

Blood availability in hospitals is of high humanitarian importance, thus blood shortage is not desired at all. High wastage rate of blood in hospitals is an important issue, which becomes more important as the standards of health care services becomes higher. In order to address blood shortage and wastage issues in a hospital, this paper develops a new inventory management model as a decision making tool to help making tactical and operational level decisions for a Hospital Blood Bank (HBB) inventory management. These decisions include issuance and ordering policy and the aim of the model is to reduce blood wastage and shortage. For this purpose, a multi period, multi-product inventory... 

This paper models the cyber-social system as a cyber-network of agents monitoring states of individuals in a social network. The state of each individual is represented by a social node, and the interactions among individuals are represented by a social link. In the cyber-network, each node represents an agent, and the links represent information sharing among agents. The agents make an observation of social states and perform distributed inference. In this direction, the contribution of this paper is threefold: First, a novel distributed inference protocol is proposed that makes no assumption on the rank of the underlying social system. This is significant as most protocols in the... 

Cloud systems empower the big data management by providing virtual machines (VMs) to process data nodes (DNs) in a faster, cheaper and more effective way. The efficiency of a VM allocation is an important concern that is influenced by the communication latencies. In the literature, it has been proved that the VM assignment minimizing communication latency in the presence of the triangle inequality is 2-approximation. However, a 2-approximation solution is not efficient enough as data center networks are not limited to the triangle inequality. In this paper, we define the quadrilateral inequality property for latencies such that the time complexity of the VM assignment problem minimizing... 

0–1 knapsack problem (KP01) is one of the classic variants of knapsack problems in which the aim is to select the items with the total profit to be in the knapsack. In contrast, the constraint of the maximum capacity of the knapsack is satisfied. KP01 has many applications in real-world problems such as resource distribution, portfolio optimization, etc. The purpose of this work is to gather the latest SA-based solvers for KP01 together and compare their performance with the state-of-the-art meta-heuristics in the literature to find the most efficient one(s). This paper not only studies the introduced and non-introduced single-solution SA-based algorithms for KP01 but also proposes a new... 

Caching at network edges has attracted more and more research interests recently for the purpose of alleviating the network traffic pressure especially in backhaul links and improving user experience. We study Heterogeneous Cellular Caching Networks (HCCNs) consisting of macro cells in which $N$ small cell base stations (SBSs) equipped with cache memory operate in conjunction with the macro cell base station (MBS). We provide closed-form expressions of the MBS and SBSs utilization factors and average user-experienced-delay in HCCNs with overlapping coverage regions, considering general traffic models for the request arrivals based on the Independent Reference Model (IRM) and renewal traffic... 

Reactive power dispatch in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. In an open electricity market reactive power support is an ancillary service for real power transportation. From the viewpoint of ISO, this paper provides a dispatching reactive power model, based on optimal power flow, by which both the cost of procuring reactive power as auxiliary service and the losses of active power are minimized. In this paper the cost of reactive power support consists of two components: reactive power cost of generators and shunt capacitors. In addition an extremely powerful differential evolution... 

In this paper, the problem of scheduling commercial messages during the peak of viewing time of a TV channel is formulated as a combinatorial auction-based mathematical programming model. Through this model, a profitable and efficient mechanism for allocating the advertising time to advertisers is developed by which the revenue of TV channels is maximised while the effectiveness of advertising is increased. We developed a steady-state genetic algorithm to find an optimal or a near optimal solution for the proposed problem. A computational experiment was conducted for evaluating the efficiency of the proposed algorithm. A set of test problems with different sizes were generated, using the... 

Abstract Network on Chip (NoC) is an appropriate and scalable solution for today's System on Chips (SoCs) with the high communication demands. Application specific NoCs is preferable since they can be customized to optimize all requirements of the specific applications. This paper presents an OPtimization technique for Application specifIC NoCs (OPAIC), which aims not only to decrease the energy consumption but also to improve the area of NoCs. OPAIC is composed of three stages to find the optimum NoC; in the first stage, it uses a linearized form of a Quadratic Assignment Problem (QAP) to map tasks on cores to minimize the energy. In the second stage, a Mixed Integer Linear Problem (MILP)... 

Over the last decades, several approaches have been proposed in the literature to incorporate users' perceptions of travel costs, their bounded rationality, and risk-taking behaviors into network equilibrium modeling for traffic assignment problem. While theoretically advanced, these models often suffer from high complexity and computational cost and often involve parameters that are difficult to estimate. This study proposes an alternative approach where users' imprecise perceptions of travel times are endogenously constructed as fuzzy sets based on the probability distributions of random link travel times. Two decision rules are proposed accordingly to account for users' heterogeneous... 

Process planning (PP) has an important role in manufacturing systems design and operations. Volume decomposition and machinable volumes (MVs) or machining features determination is the core activity in process planning. This process requires extraction of elementary volumes (EVs), merging or clustering EVs to construct feasible MVs and finally selecting an optimal combination of MVs. Development of MVs is an important activity, so that better solution is obtained by better developed MVs. Generation of limited number of MVs or machining features, which is often performed by experts may miss the optimal solution. Also, using exact methods such as combinatorial optimization not only generate... 

This paper studies how to optimally embed a general metric, represented by a graph, into a target space while preserving the relative magnitudes of most distances. More precisely, in an ordinal embedding, we must preserve the relative order between pairs of distances (which pairs are larger or smaller), and not necessarily the values of the distances themselves. The relaxation of an ordinal embedding is the maximum ratio between two distances whose relative order is inverted by the embedding. We develop polynomial-time constant-factor approximation algorithms for minimizing the relaxation in an embedding of an unweighted graph into a line metric and into a tree metric. These two basic target... 

One of the most critical issues in manufacturing systems is the operator management. In this paper, the operator assignment problem is studied within a cellular manufacturing system. The most important novelty of this research is the consideration of operator learning and forgetting effects simultaneously. The skill level of an operator can be increased/decreased based on the time spent on a machine. Moreover, the issues related to operators like hiring, firing, and salaries are considered in the proposed model. The parameters are considered to be uncertain in this model, and a robust optimization approach is developed to handle it. Using this approach, the model solution remains feasible...