Sharif Digital Repository

A new weighted order scheme is presented for finding alternative Pareto optimal solution of multi objective linear programming problems. In developing the weighted scheme, a big M model is proposed. We establish some properties of the ordering scheme and the proposed model and show how to determine proper values of the parameter M. Illustrative examples are worked out to show the effectiveness of the proposed approach and the competitiveness of the obtained solutions as compared to the ones obtained by the weighted maxmin and the weighted aggregation methods  

Motivated by the bus escape routing problem in printed circuit boards, we study the following rectangle escape problem: given a set S of n axis-aligned rectangles inside an axis-aligned rectangular region R, extend each rectangle in S toward one of the four borders of R so that the maximum density over the region R is minimized. The density of each point p∈R is defined as the number of extended rectangles containing p. We show that the problem is hard to approximate to within a factor better than 3/2 in general. When the optimal density is sufficiently large, we provide a randomized algorithm that achieves an approximation factor of 1+ε with high probability improving over the current best... 

This paper presents an improved firefly algorithm (FA) for fast optimization of truss structures with discrete variables. The enhanced accelerated firefly algorithm (AFA) is a simple, but very effective modification of FA. In order to investigate the performance and robustness of the proposed algorithm, some benchmark (structural optimization) problems are solved and the results are compared with FA and other algorithms. The results show that in some test cases, AFA not only finds lighter structures compared to other algorithms, but also converges faster. In the rest test cases, the optimal solutions are found with very less computational effort. The study also shows that the proposed AFA... 

In this paper, a novel steganographic method is proposed which is based on the spatial domain: Least Significant Bit (LSB). The LSB matching method proposed by Mielikainen utilizes a binary function to reduce the number of changed pixel values. While in this paper a bipolar evaluating system is proposed to assess the performance of different orders for LSB matching. Afterward a genetic algorithm strategy is employed to search for an optimal solution among all the permutation orders. The experimental results show that by employing the proposed bipolar evaluating system, the distortion of the stego-image is reduced while the probability of detection is decreased  

This study proposes an imperialist competition algorithm (ICA) to maximise the benefits of distribution network operators (DNOs) because of the existence of distributed generation (DG) units. The sum of active loss reduction and network investment deferral incentives has been considered as the objective function to be maximised in this study. The optimal location and size of DG units in the network are found considering various techno-economical issues. The application of the proposed methodology in the UK under current Ofgem financial incentives for DNOs is investigated. The ability of the proposed approach in finding the optimal solution is validated by comparing the obtained results with... 

This paper presents a special case of the general shop called stage shop problem. The stage shop is a more realistic generalization of the mixed shop problem. In the stage shop problem, each job has several stages of operations. In order to solve the stage shop problem with makespan objective function, an existing neighborhood of job shop is used. In this neighborhood, few enhanced conditions are proposed to prevent cycle generation. In addition, a new neighborhood for operations that belong to the same job is presented. These neighborhoods are applied to the stage shop problem in a tabu search framework. A genetic algorithm is used to obtain good initial solutions. An existing lower bound... 

To formulate stochastic capacity allocation problems in a manufacturing system, the concept and techniques of revenue management is applied in this research. It is assumed the production capacity is stochastic and hence its exact size cannot be forecasted in advance, at the time of planning. There are two classes of "frequent" and "occasional" customers demanding this capacity. The price rate as well as the penalty for order cancellation caused by overbooking is different for each class. The model is developed mathematically and we propose an analytical solution method. The properties of the optimal solution as well as the behavior of objective function are also analyzed. The objective... 

In this paper we claim that local optimization can produce proper start point for genetic search. We completely test this claim on partitioning problem and on the performance of genetic search in a real problem that is finding aggregation tree in the sensor networks. The presented method (named Tendency algorithm) increases the performance of heuristic searches, and can be used in parallel with other tuning methods. The paper justifies the logic behind tendency algorithm by measuring the "entropy" of solution (in regard to optimal solution), and by numerous empirical tests. © 2008 IEEE  

Single-Row Facility Layout Problem (SRFLP) is a http://library.sharif.ir/web-manage/catalog/resource.do?method=edit&flowLastAction=view&id=447751special class of facilitylayout problems, consists of finding an optimal linear placement of rectangularfacilities with varying dimensions on a straight line. In this research, wefirst present a theorem to find the optimal solution of a special case of SRFLP.The results obtained by this theorem are very useful in reducing thecomputational efforts when, later on, a new algorithm based on tabu search ispresented for SRFLP. Computational results of the proposed algorithm onbenchmark problems show the efficiency of the algorithm compared to the... 

Many companies regularly run Big Data analysis, and need to optimize their resource usage considering cost, deadline, and environmental impact simultaneously. The cloud allows choosing from various virtual machines (VM) where the number and type of VMs affect the outcome such as the time for data placement and data shuffle phases, a task's energy consumption and execution time, and the makespan of jobs. We provide provisioning and scheduling algorithms to minimize environmental impact, considering the above factors, for frequently executed MapReduce jobs. To mathematically model the problem and obtain the optimal solution, we present an Integer Linear Programming (ILP) model and then... 

This letter proposes an analytic framework for achieving an optimal solution for phasor measurement unit (PMU) placement problem. The proposed technique is on the basis of the cost/benefit analysis while long-term economic aspects and existing technical issues are simultaneously accounted for. More deployment of PMU devices would result in more reliable and secure electricity services. The reduction of system risk cost is hence recognized as the benefit associated with the development of wide-area measurement system (WAMS). The optimal number and location of PMUs are determined such that adding more PMUs is no longer beneficial. Two systems are examined to demonstrate the performance of the... 

In this paper, a seasonal multi-product multi-period inventory control problem is modeled in which the inventory costs are obtained under inflation and all-unit discount policy. Furthermore, the products are delivered in boxes of known number of items, and in case of shortage, a fraction of demand is considered backorder and a fraction lost sale. Besides, the total storage space and total available budget are limited. The objective is to find the optimal number of boxes of the products in different periods to minimize the total inventory cost (including ordering, holding, shortage, and purchasing costs). Since the integer nonlinear model of the problem is hard to solve using exact methods, a... 

Deployment of low-power low-cost small access points such as femtocell access points (FAPs) constitute an attractive solution for improving the existing macrocell access points' (MAPs) capacity, reliability, and coverage. However, FAP deployment faces challenging problems such as interference management and the lack of flexible frameworks for deploying the FAPs by the service providers (SPs). In this paper, we propose a novel solution that jointly associates the user equipment (UE) to the APs, and allocates the FAPs to the SPs such that the the total satisfaction of the UEs in an uplink OFDMA network is maximized. We model the competitive behaviors among the UEs, FAPs, and SPs as a dynamic... 

In this paper, we address a basic production planning problem with price dependent demand and stochastic yield of production. We use price and target quantity as decision variables to lower the risk of low yield. The value of risk control becomes more important especially for products with short life cycle. This is because, the profit implications of low yield might be unbearable in the short run. We apply Conditional Value at Risk (CVaR) to model the risk. CVaR measure is a coherent risk measure and thereby having nice conceptual and mathematical underpinnings. It is also widely used in practice. We consider the problem under general demand function and general distribution function of... 

In this letter, both the number of participating nodes and spatial dispersion are incorporated to establish a bi-objective optimization problem for maximizing the quality of aggregation under interference and delay constraints in tree-based wireless sensor networks (WSNs). The formulated problem is proved to be NP-hard with respect to Weighted-sum scalarization and a distributed heuristic aggregation scheduling algorithm, named SDMAX, is proposed. Simulation results show that SDMAX not only gives a close approximation of the Pareto-optimal solution, but also outperforms the best, to our knowledge, existing alternative proposed so far in the literature  

Aircraft landing problem is to assign an airport's runways to the arrival aircrafts as well as to schedule the landing time of these aircrafts. In this paper, first a mixed integer goal programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design a hybrid meta-heuristic applying simulated annealing framework. The computational results show that the proposed algorithm can obtain the optimal solution for instances up to 100 aircrafts, and also it is capable of finding very high quality and comparable solutions for the problems with up to 500 aircrafts and 5 runways in a short time  

This article presents a new model for pricing a new product considering a skimming pricing strategy in the presence of competition. We consider two periods for price setting, including skimming and an economy period. The problem is to decide on skimming as well as economy price, in order to maximize total profit. The derived model is a non-linear programming model and we have analyzed the structure and properties of an optimal solution to develop a solution method. Analytical results, as well as managerial insights, are presented by mathematical and numerical analyses  

This letter proposes an analytic framework for achieving an optimal solution for phasor measurement unit (PMU) placement problem. The proposed technique is on the basis of the cost/benefit analysis while long-term economic aspects and existing technical issues are simultaneously accounted for. More deployment of PMU devices would result in more reliable and secure electricity services. The reduction of system risk cost is hence recognized as the benefit associated with the development of wide-area measurement system (WAMS). The optimal number and location of PMUs are determined such that adding more PMUs is no longer beneficial. Two systems are examined to demonstrate the performance of the... 

In this paper, we consider the restricted version of the well-known 2D line simplification problem under area measures and for restricted version. We first propose a unified definition for both of sum-area and difference-area measures that can be used on a general path of n vertices. The optimal simplification runs in O(n 3) under both of these measures. Under sum-area measure and for a realistic input path, we propose an approximation algorithm of O n2 time complexity to find a simplification of the input path, where is the absolute error of this algorithm compared to the optimal solution. Furthermore, for difference-area measure, we present an algorithm that finds the optimal...