Advances in Operations Research The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. Linear Integer Model for the Course Timetabling Problem of a Faculty in Rio de Janeiro Wed, 20 Jan 2016 07:33:58 +0000 This work presents a linear integer programming model that solves a timetabling problem of a faculty in Rio de Janeiro, Brazil. The model was designed to generate solutions that meet the preferences of the faculty’s managers, namely, allocating the maximum number of lecturers with highest academic title and minimising costs by merging courses with equivalent syllabuses. The integer linear model also finds solutions that meet lecturers’ scheduling preferences, thereby generating more practical and comfortable schedules for these professionals. Preferences were represented in the objective function, each with a specific weight. The model outperformed manual solutions in terms of response time and quality. The model was also able to demonstrate that lecturers’ scheduling preferences are actually conflicting goals. The model was approved by the faculty’s managers and has been used since the second semester of 2011. Valdecy Pereira and Helder Gomes Costa Copyright © 2016 Valdecy Pereira and Helder Gomes Costa. All rights reserved. Decision Support for Flexible Liner Shipping Sun, 10 Jan 2016 06:47:51 +0000 We present a transportation problem representing a combination of liner and tramp shipping, where using other modes of transportation is also an option. As an example, we consider transportation of palletized frozen fish from Russia and Norway to terminals in Norway, the Netherlands, and the UK. We present a mathematical model for the planning problem associated with each tour and show that problem instances of realistic size can be solved to optimality using standard software. Johan Oppen Copyright © 2016 Johan Oppen. All rights reserved. Two New Reformulation Convexification Based Hierarchies for 0-1 MIPs Sun, 29 Nov 2015 13:03:33 +0000 First, we introduce two new reformulation convexification based hierarchies called RTC and RSC for which the rank continuous relaxations are denoted by and , respectively. These two hierarchies are obtained using two different convexification schemes: term convexification in the case of the RTC hierarchy and standard convexification in the case of the RSC hierarchy. Secondly, we compare the strength of these two hierarchies. We will prove that (i) the hierarchy RTC is equivalent to the RLT hierarchy of Sherali-Adams, (ii) the hierarchy RTC dominates the hierarchy RSC, and (iii) the hierarchy RSC is dominated by the Lift-and-Project hierarchy. Thirdly, for every rank , we will prove that and where the sets and are convex, while and are two nonconvex sets with empty interior (all these sets depend on the convexification step). The first inclusions allow, in some cases, an explicit characterization (in the space of the original variables) of the RLT relaxations. Finally, we will discuss weak version of both RTC and RSC hierarchies and we will emphasize some connections between them. Hacene Ouzia Copyright © 2015 Hacene Ouzia. All rights reserved. Bat Algorithm Based Hybrid Filter-Wrapper Approach Thu, 08 Oct 2015 15:31:31 +0000 This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI. In BAMI, MI was used to identify promising features which could potentially accelerate the process of finding the best known solution. The promising features were then used to replace several of the randomly selected features during the search initialization. BAMI was tested over twelve datasets and compared against the standard Bat Algorithm guided by Naive Bayes (BANV). The results showed that BAMI outperformed BANV in all datasets in terms of computational time. The statistical test indicated that BAMI has significantly lower computational time than BANV in six out of twelve datasets, while maintaining the effectiveness. The results also showed that BAMI performance was not affected by the number of features or samples in the dataset. Finally, BAMI was able to find the best known solutions with limited number of iterations. Ahmed Majid Taha, Soong-Der Chen, and Aida Mustapha Copyright © 2015 Ahmed Majid Taha et al. All rights reserved. Queue Length and Server Content Distribution in an Infinite-Buffer Batch-Service Queue with Batch-Size-Dependent Service Sun, 04 Oct 2015 16:34:48 +0000 We analyze an infinite-buffer batch-size-dependent batch-service queue with Poisson arrival and arbitrarily distributed service time. Using supplementary variable technique, we derive a bivariate probability generating function from which the joint distribution of queue and server content at departure epoch of a batch is extracted and presented in terms of roots of the characteristic equation. We also obtain the joint distribution of queue and server content at arbitrary epoch. Finally, the utility of analytical results is demonstrated by the inclusion of some numerical examples which also includes the investigation of multiple zeros. U. C. Gupta and S. Pradhan Copyright © 2015 U. C. Gupta and S. Pradhan. All rights reserved. Novel Interior Point Algorithms for Solving Nonlinear Convex Optimization Problems Wed, 16 Sep 2015 06:14:30 +0000 This paper proposes three numerical algorithms based on Karmarkar’s interior point technique for solving nonlinear convex programming problems subject to linear constraints. The first algorithm uses the Karmarkar idea and linearization of the objective function. The second and third algorithms are modification of the first algorithm using the Schrijver and Malek-Naseri approaches, respectively. These three novel schemes are tested against the algorithm of Kebiche-Keraghel-Yassine (KKY). It is shown that these three novel algorithms are more efficient and converge to the correct optimal solution, while the KKY algorithm fails in some cases. Numerical results are given to illustrate the performance of the proposed algorithms. Sakineh Tahmasebzadeh, Hamidreza Navidi, and Alaeddin Malek Copyright © 2015 Sakineh Tahmasebzadeh et al. All rights reserved. An Empirical Study of Strategic Positioning and Production Efficiency Mon, 22 Jun 2015 11:51:20 +0000 We examine the relationship between strategic positioning of firms and their production efficiency. Firms with competitive advantages based on either cost leadership or differentiation are able to outperform their competitors. Firms pursuing a cost leadership strategy seek to be the lowest cost producer, primarily by minimizing inputs for a given level of output, thus concentrating on increasing the efficiency of their production processes. On the other hand, firms that pursue a differentiation strategy rely on innovation, brand development, marketing, and so forth to achieve competitive advantages; therefore such firms do not place high emphasis on production efficiency. Thus the importance of production efficiency for the success of a firm depends on the strategic positioning of the firm. We apply DEA to an archival data for a large sample of publicly listed firms to investigate the importance of production efficiency for firms based on their strategic positioning. We provide empirical evidence that firms pursuing a cost leadership strategy attribute higher importance to production efficiency, while firms pursuing differentiation strategy attribute less importance to production efficiency. Hsihui Chang, Guy D. Fernando, and Arindam Tripathy Copyright © 2015 Hsihui Chang et al. All rights reserved. Optimal Switching Strategy between Admission Control and Pricing Control Policies with Two Types of Customers and Search Costs Mon, 30 Mar 2015 07:45:43 +0000 This paper presents a switching strategy between the admission control and the pricing control policies in a queueing system with two types of customers. For an arriving first-type customer, the decision maker has an option on which policy to choose between the two control policies; that is, one determines whether or not to admit the customer’s request for the service (admission control) or decides a price of the customer’s request and offers it to the customer (pricing control). The second-type customers are only served when no first-type customers are present in the system in order to prevent the system from being idle. This would yield an extra income, which we refer to as the sideline profit. The so-called search cost, which is a cost paid to search for customers, creates the search option on whether to continue the search or not. We clarify the properties of the optimal switching strategy as well as the optimal search policy in relation to the sideline profit in order to maximize the total expected net profit. In particular, we show that when the sideline profit is sufficiently large, the two optimal switching thresholds exist with respect to the number of first-type customers in the system. Jae-Dong Son Copyright © 2015 Jae-Dong Son. All rights reserved. Scheduling Jobs Families with Learning Effect on the Setup Thu, 19 Feb 2015 07:10:47 +0000 The present paper aims to address the flow-shop sequence-dependent group scheduling problem with learning effect (FSDGSLE). The objective function to be minimized is the total completion time, that is, the makespan. The workers are required to carry out manually the set-up operations on each group to be loaded on the generic machine. The operators skills improve over time due to the learning effects; therefore the set-up time of a group under learning effect decreases depending on the order the group is worked in. In order to effectively cope with the issue at hand, a mathematical model and a hybrid metaheuristic procedure integrating features from genetic algorithms (GA) have been developed. A well-known problem benchmark risen from literature, made by two-, three- and six-machine instances, has been taken as reference for assessing performances of such approach against the two most recent algorithms presented by literature on the FSDGS issue. The obtained results, also supported by a properly developed ANOVA analysis, demonstrate the superiority of the proposed hybrid metaheuristic in tackling the FSDGSLE problem under investigation. Sergio Fichera, Antonio Costa, and Fulvio Cappadonna Copyright © 2015 Sergio Fichera et al. All rights reserved. Preventive Maintenance Scheduling for Multicogeneration Plants with Production Constraints Using Genetic Algorithms Tue, 10 Feb 2015 09:09:27 +0000 This paper describes a method developed to schedule the preventive maintenance tasks of the generation and desalination units in separate and linked cogeneration plants provided that all the necessary maintenance and production constraints are satisfied. The proposed methodology is used to generate two preventing maintenance schedules, one for electricity and the other for distiller. Two types of crossover operators were adopted, 2-point and 4-point. The objective function of the model is to maximize the available number of operational units in each plant. The results obtained were satisfying the problem parameters. However, 4-point slightly produce better solution than 2-point ones for both electricity and water distiller. The performance as well as the effectiveness of the genetic algorithm in solving preventive maintenance scheduling is applied and tested on a real system of 21 units for electricity and 21 units for water. The results presented here show a great potential for utility applications for effective energy management over a time horizon of 52 weeks. The model presented is an effective decision tool that optimizes the solution of the maintenance scheduling problem for cogeneration plants under maintenance and production constraints. Khaled Alhamad, Mohsen Alardhi, and Abdulla Almazrouee Copyright © 2015 Khaled Alhamad et al. All rights reserved. Passenger Traffic Evaluation and Price Formation on the Transportation Services Market Tue, 03 Feb 2015 06:47:25 +0000 This paper investigates equilibrium formation in the passenger traffic model. First, we propose an estimation technique for the distribution of incoming passengers at each stop with respect to subsequent stops of a route based on available information on incoming and outgoing passengers. Second, we employ the obtained information on passenger traffic to introduce a game-theoretic model of passenger traffic distribution with respect to transport facilities. V. M. Bure, V. V. Mazalov, A. V. Melnik, and N. V. Plaksina Copyright © 2015 V. M. Bure et al. All rights reserved. Analysis of a Multiserver Queueing-Inventory System Tue, 20 Jan 2015 08:21:37 +0000 We attempt to derive the steady-state distribution of the queueing-inventory system with positive service time. First we analyze the case of servers which are assumed to be homogeneous and that the service time follows exponential distribution. The inventory replenishment follows the policy. We obtain a product form solution of the steady-state distribution under the assumption that customers do not join the system when the inventory level is zero. An average system cost function is constructed and the optimal pair and the corresponding expected minimum cost are computed. As in the case of retrial queue with , we conjecture that for , queueing-inventory problems, do not have analytical solution. So we proceed to analyze such cases using algorithmic approach. We derive an explicit expression for the stability condition of the system. Conditional distribution of the inventory level, conditioned on the number of customers in the system, and conditional distribution of the number of customers, conditioned on the inventory level, are derived. The distribution of two consecutive to transitions of the inventory level (i.e., the first return time to ) is computed. We also obtain several system performance measures. A. Krishnamoorthy, R. Manikandan, and Dhanya Shajin Copyright © 2015 A. Krishnamoorthy et al. All rights reserved. A Hybrid Grey Relational Analysis and Nondominated Sorting Genetic Algorithm-II for Project Portfolio Selection Wed, 24 Dec 2014 09:07:29 +0000 Project selection and formation of an optimal portfolio of selected projects are among the main challenges of project management. For this purpose, several factors and indicators are simultaneously examined considering the terms and conditions of the decision problem. Obviously, both qualitative and quantitative factors may influence the formation of a portfolio of projects. In this study, the projects were first ranked using grey relational analysis to form an optimal portfolio of projects and to create an expert system for the final project selection. Because of the fuzzy nature of the environmental risk of each project, the environmental risk was predicted and analyzed using the fuzzy inference system and failure mode and effect analysis based on fuzzy rules. Then, the rank and risk of each project were optimized using a two-objective zero-one mathematical programming model considering the practical constraints of the decision problem through the nondominated sorting genetic algorithm-II (NSGA-II). A case study was used to discuss the practical methodology for selecting a portfolio of projects. Farshad Faezy Razi Copyright © 2014 Farshad Faezy Razi. All rights reserved. Selection of Vendor Based on Intuitionistic Fuzzy Analytical Hierarchy Process Wed, 10 Dec 2014 07:29:42 +0000 Business environment is characterized by greater domestic and international competitive position in the global market. Vendors play a key role in achieving the so-called corporate competition. It is not easy however to identify good vendors because evaluation is based on multiple criteria. In practice, for VSP most of the input information about the criteria is not known precisely. Intuitionistic fuzzy set is an extension of the classical fuzzy set theory (FST), which is a suitable way to deal with impreciseness. In other words, the application of intuitionistic fuzzy sets instead of fuzzy sets means the introduction of another degree of freedom called nonmembership function into the set description. In this paper, we proposed a triangular intuitionistic fuzzy number based approach for the vendor selection problem using analytical hierarchy process. The crisp data of the vendors is represented in the form of triangular intuitionistic fuzzy numbers. By applying AHP which involves decomposition, pairwise comparison, and deriving priorities for the various levels of the hierarchy, an overall crisp priority is obtained for ranking the best vendor. A numerical example illustrates our method. Lastly a sensitivity analysis is performed to find the most critical criterion on the basis of which vendor is selected. Prabjot Kaur Copyright © 2014 Prabjot Kaur. All rights reserved. Mathematical Analysis of Queue with Phase Service: An Overview Wed, 10 Dec 2014 00:10:08 +0000 We discuss various aspects of phase service queueing models. A large number of models have been developed in the area of queueing theory incorporating the concept of phase service. These phase service queueing models have been investigated for resolving the congestion problems of many day-to-day as well as industrial scenarios. In this survey paper, an attempt has been made to review the work done by the prominent researchers on the phase service queues and their applications in several realistic queueing situations. The methodology used by several researchers for solving various phase service queueing models has also been described. We have classified the related literature based on modeling and methodological concepts. The main objective of present paper is to provide relevant information to the system analysts, managers, and industry people who are interested in using queueing theory to model congestion problems wherein the phase type services are prevalent. Richa Sharma Copyright © 2014 Richa Sharma. All rights reserved. Production Scheduling of Open Pit Mines Using Particle Swarm Optimization Algorithm Tue, 25 Nov 2014 11:45:44 +0000 Determining an optimum long term production schedule is an important part of the planning process of any open pit mine; however, the associated optimization problem is demanding and hard to deal with, as it involves large datasets and multiple hard and soft constraints which makes it a large combinatorial optimization problem. In this paper a procedure has been proposed to apply a relatively new and computationally less expensive metaheuristic technique known as particle swarm optimization (PSO) algorithm to this computationally challenging problem of the open pit mines. The performance of different variants of the PSO algorithm has been studied and the results are presented. Asif Khan and Christian Niemann-Delius Copyright © 2014 Asif Khan and Christian Niemann-Delius. All rights reserved. An Optimization Model for Product Placement on Product Listing Pages Tue, 11 Nov 2014 11:43:20 +0000 The design of product listing pages is a key component of Website design because it has significant influence on the sales volume on a Website. This study focuses on product placement in designing product listing pages. Product placement concerns how venders of online stores place their products over the product listing pages for maximization of profit. This problem is very similar to the offline shelf management problem. Since product information sources on a Web page are typically communicated through the text and image, visual stimuli such as color, shape, size, and spatial arrangement often have an effect on the visual attention of online shoppers and, in turn, influence their eventual purchase decisions. In view of the above, this study synthesizes the visual attention literature and theory of shelf-space allocation to develop a mathematical programming model with genetic algorithms for finding optimal solutions to the focused issue. The validity of the model is illustrated with example problems. Yan-Kwang Chen, Fei-Rung Chiu, and Ciao-Jyun Yang Copyright © 2014 Yan-Kwang Chen et al. All rights reserved. Lot Size Decisions for Vendor-Buyer System with Quantity Discount, Partial Backorder, and Stochastic Demand Tue, 11 Nov 2014 00:00:00 +0000 This paper presents production-inventory model for two-echelon system consisting of single vendor and single buyer. The proposed model contributes to the current inventory literature by incorporating quantity discount scheme into stochastic vendor-buyer model. Almost all vendor-buyer inventory models have discussed this scheme in single-echelon system and deterministic demand situation. Here, we assume that the demand of the buyer is normally distributed and the unmet demand is considered to be partially backordered. In addition, the lead time is variable and consists of production time and nonproductive time. The quantity discount is developed by using all-units quantity discounts. Finally, an iterative procedure is proposed to obtain all decision variables and numerical examples are provided to show the application of the proposed procedure. Wakhid Ahmad Jauhari Copyright © 2014 Wakhid Ahmad Jauhari. All rights reserved. Heuristic-Based Firefly Algorithm for Bound Constrained Nonlinear Binary Optimization Wed, 08 Oct 2014 09:48:25 +0000 Firefly algorithm (FA) is a metaheuristic for global optimization. In this paper, we address the practical testing of a heuristic-based FA (HBFA) for computing optima of discrete nonlinear optimization problems, where the discrete variables are of binary type. An important issue in FA is the formulation of attractiveness of each firefly which in turn affects its movement in the search space. Dynamic updating schemes are proposed for two parameters, one from the attractiveness term and the other from the randomization term. Three simple heuristics capable of transforming real continuous variables into binary ones are analyzed. A new sigmoid “erf” function is proposed. In the context of FA, three different implementations to incorporate the heuristics for binary variables into the algorithm are proposed. Based on a set of benchmark problems, a comparison is carried out with other binary dealing metaheuristics. The results demonstrate that the proposed HBFA is efficient and outperforms binary versions of differential evolution (DE) and particle swarm optimization (PSO). The HBFA also compares very favorably with angle modulated version of DE and PSO. It is shown that the variant of HBFA based on the sigmoid “erf” function with “movements in continuous space” is the best, in terms of both computational requirements and accuracy. M. Fernanda P. Costa, Ana Maria A. C. Rocha, Rogério B. Francisco, and Edite M. G. P. Fernandes Copyright © 2014 M. Fernanda P. Costa et al. All rights reserved. Multimode Preemptive Resource Investment Problem Subject to Due Dates for Activities: Formulation and Solution Procedure Mon, 29 Sep 2014 11:48:00 +0000 The preemptive Multimode resource investment problem is investigated. The Objective is to minimize the total renewable/nonrenewable resource costs and earliness-tardiness costs by a given project deadline and due dates for activities. In this problem setting preemption is allowed with no setup cost or time. The project contains activities interrelated by finish-start type precedence relations with a time lag of zero, which require a set of renewable and nonrenewable resources. The problem formed in this way is an NP-hard. A mixed integer programming formulation is proposed for the problem and parameters tuned genetic algorithm (GA) is proposed to solve it. To evaluate the performance of the proposed algorithm, 120 test problems are used. Comparative statistical results reveal that the proposed GA is efficient and effective in terms of the objective function and computational times. Behrouz Afshar-Nadjafi and Mohammad Arani Copyright © 2014 Behrouz Afshar-Nadjafi and Mohammad Arani. All rights reserved. Algorithms for Location Problems Based on Angular Distances Thu, 25 Sep 2014 11:19:55 +0000 This paper describes four mathematical models for the single-facility location problems based on four special distance metrics and algorithms for solving such problems. In this study, algorithms of solving Weber problems using four distance predicting functions (DPFs) are proposed in accordance with four strategies for manipulator control. A numerical example is presented in this proposal as an analytical proof of the optimality of their results. Lev A. Kazakovtsev, Predrag S. Stanimirović, Idowu A. Osinuga, Mikhail N. Gudyma, and Alexander N. Antamoshkin Copyright © 2014 Lev A. Kazakovtsev et al. All rights reserved. The Supplying Chain Scheduling with the Cost Constraint and Subcontracting Tue, 02 Sep 2014 12:26:58 +0000 We propose an analytical scheduling model with subcontracting. Each job can be processed either on a single machine at a manufacturer or outsourced to a subcontractor, possibly at a higher cost. For a given set of jobs, the decisions the manufacturer needs to make include the selection of a subset of jobs to be outsourced and the schedule of all the jobs. The objective functions are to minimize the commonly used scheduling measures, subject to a constraint on the total production and subcontracting cost. We show the NP-hardiness for the problems with different objective functions and develop dynamic programming algorithms for solving them. Guo Sun and Liying Yu Copyright © 2014 Guo Sun and Liying Yu. All rights reserved. On One Approach to TSP Structural Stability Thu, 26 Jun 2014 08:12:01 +0000 In this paper we study an inverse approach to the traveling salesman reoptimization problem. Namely, we consider the case of the addition of a new vertex to the initial TSP data and fix the simple “adaptation” algorithm: the new vertex is inserted into an edge of the optimal tour. In the paper we consider the conditions describing the vertexes that can be inserted by this algorithm without loss of optimality, study the properties of stability areas, and address several model applications. Evgeny Ivanko Copyright © 2014 Evgeny Ivanko. All rights reserved. Combining Diffusion Models and Macroeconomic Indicators with a Modified Genetic Programming Method: Implementation in Forecasting the Number of Mobile Telecommunications Subscribers in OECD Countries Mon, 16 Jun 2014 13:12:48 +0000 This paper proposes a modified Genetic Programming method for forecasting the mobile telecommunications subscribers’ population. The method constitutes an expansion of the hybrid Genetic Programming (hGP) method improved by the introduction of diffusion models for technological forecasting purposes in the initial population, such as the Logistic, Gompertz, and Bass, as well as the Bi-Logistic and LogInLog. In addition, the aforementioned functions and models expand the function set of hGP. The application of the method in combination with macroeconomic indicators such as Gross Domestic Product per Capita (GDPpC) and Consumer Prices Index (CPI) leads to the creation of forecasting models and scenarios for medium- and long-term level of predictability. The forecasting module of the program has also been improved with the multi-levelled use of the statistical indices as fitness functions and model selection indices. The implementation of the modified-hGP in the datasets of mobile subscribers in the Organisation for Economic Cooperation and Development (OECD) countries shows very satisfactory forecasting performance. Konstantinos Salpasaranis, Vasilios Stylianakis, and Stavros Kotsopoulos Copyright © 2014 Konstantinos Salpasaranis et al. All rights reserved. Disaggregation of Statistical Livestock Data Using the Entropy Approach Tue, 03 Jun 2014 08:08:03 +0000 A process of agricultural data disaggregation is developed to address the lack of updated disaggregated data concerning main livestock categories at subregional and county level in the Alentejo Region, southern Portugal. The model developed considers that the number of livestock units is a function of the agricultural and forest occupation, and data concerning the existing agricultural and forest occupation, as well as the conversion of livestock numbers into normal heads, are needed in order to find this relation. The weight of each livestock class is estimated using a dynamic process based on a generalized maximum entropy model and on a crossentropy minimization model, which comprises two stages. The model was applied to the county of Castelo de Vide and their results were validated in cross reference to real data from different sources. António Xavier, Maria de Belém Costa Freitas, and Rui Fragoso Copyright © 2014 António Xavier et al. All rights reserved. A Mathematical Model for Optimizing Organizational Learning Capability Mon, 05 May 2014 12:34:01 +0000 Learning capability is the basis of evolution in every organization. Since the simplification and development of learning level in any organization seems to be necessary, in this paper we represent a mathematical model to maximize organizational learning capability. The proposed mathematical model focuses on required cost, labor, and capital, for implementation of ten effective factors on learning capability in different parts of an organization so that they are effective in learning capability with least cost for organization. To measure the factors in different parts of an organization some metrics are introduced. Computational tests confirm the effectiveness of the model. The model is optimized by epsilon constraint while it is multiobjective one. The validation of the model is also reported to emphasize the validity and applicability of the proposed methodology. Masoomeh Alikhani and Hamed Fazlollahtabar Copyright © 2014 Masoomeh Alikhani and Hamed Fazlollahtabar. All rights reserved. Resource Constrained Project Scheduling Subject to Due Dates: Preemption Permitted with Penalty Wed, 16 Apr 2014 14:08:13 +0000 Extensive research works have been carried out in resource constrained project scheduling problem. However, scarce researches have studied the problems in which a setup cost must be incurred if activities are preempted. In this research, we investigate the resource constrained project scheduling problem to minimize the total project cost, considering earliness-tardiness and preemption penalties. A mixed integer programming formulation is proposed for the problem. The resulting problem is NP-hard. So, we try to obtain a satisfying solution using simulated annealing (SA) algorithm. The efficiency of the proposed algorithm is tested based on 150 randomly produced examples. Statistical comparison in terms of the computational times and objective function indicates that the proposed algorithm is efficient and effective. Behrouz Afshar-Nadjafi Copyright © 2014 Behrouz Afshar-Nadjafi. All rights reserved. Insensitive Bounds for the Stationary Distribution of a Single Server Retrial Queue with Server Subject to Active Breakdowns Mon, 24 Mar 2014 07:29:23 +0000 The paper addresses monotonicity properties of the single server retrial queue with no waiting room and server subject to active breakdowns. The obtained results allow us to place in a prominent position the insensitive bounds for the stationary distribution of the embedded Markov chain related to the model in the study. Numerical illustrations are provided to support the results. Mohamed Boualem Copyright © 2014 Mohamed Boualem. All rights reserved. Benchmarking in Data Envelopment Analysis: An Approach Based on Genetic Algorithms and Parallel Programming Thu, 13 Feb 2014 12:42:30 +0000 Data Envelopment Analysis (DEA) is a nonparametric technique to estimate the current level of efficiency of a set of entities. DEA also provides information on how to remove inefficiency through the determination of benchmarking information. This paper is devoted to study DEA models based on closest efficient targets, which are related to the shortest projection to the production frontier and allow inefficient firms to find the easiest way to improve their performance. Usually, these models have been solved by means of unsatisfactory methods since all of them are related in some sense to a combinatorial NP-hard problem. In this paper, the problem is approached by genetic algorithms and parallel programming. In addition, to produce reasonable solutions, a particular metaheuristic is proposed and checked through some numerical instances. Juan Aparicio, Jose J. Lopez-Espin, Raul Martinez-Moreno, and Jesus T. Pastor Copyright © 2014 Juan Aparicio et al. All rights reserved. Optimality Conditions and Duality of Three Kinds of Nonlinear Fractional Programming Problems Wed, 27 Nov 2013 15:16:28 +0000 Some assumptions for the objective functions and constraint functions are given under the conditions of convex and generalized convex, which are based on the -convex, -convex, and -convex. The sufficiency of Kuhn-Tucker optimality conditions and appropriate duality results are proved involving -convex, -convex, and generalized -convex functions. Xiaomin Zhang and Zezhong Wu Copyright © 2013 Xiaomin Zhang and Zezhong Wu. All rights reserved.