Advances in Operations Research The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. Selective Trunk with Multiserver Reservation Thu, 19 May 2016 09:17:01 +0000 We consider a queueing model that is primarily applicable to traffic control in communication networks that use the Selective Trunk Reservation technique. Specifically, consider two traffic streams competing for service at an -server queueing system. Jobs from the protected stream, stream 1, are blocked only if all servers are busy. Jobs from the best effort stream, stream 2, are blocked if , servers are busy. Blocked jobs are diverted to a secondary group of servers with, possibly, a different service rate. We extend the literature that studied this system for the special case of and present an explicit computational scheme to calculate the joint probabilities of the number of primary and secondary busy servers and related performance measures. We also argue that the model can be useful for bed allocation in a hospital. Bacel Maddah and Muhammad El-Taha Copyright © 2016 Bacel Maddah and Muhammad El-Taha. All rights reserved. Markovian Queueing System with Discouraged Arrivals and Self-Regulatory Servers Wed, 27 Apr 2016 11:11:05 +0000 We consider discouraged arrival of Markovian queueing systems whose service speed is regulated according to the number of customers in the system. We will reduce the congestion in two ways. First we attempt to reduce the congestion by discouraging the arrivals of customers from joining the queue. Secondly we reduce the congestion by introducing the concept of service switches. First we consider a model in which multiple servers have three service rates , , and (), say, slow, medium, and fast rates, respectively. If the number of customers in the system exceeds a particular point or , the server switches to the medium or fast rate, respectively. For this adaptive queueing system the steady state probabilities are derived and some performance measures such as expected number in the system/queue and expected waiting time in the system/queue are obtained. Multiple server discouraged arrival model having one service switch and single server discouraged arrival model having one and two service switches are obtained as special cases. A Matlab program of the model is presented and numerical illustrations are given. K. V. Abdul Rasheed and M. Manoharan Copyright © 2016 K. V. Abdul Rasheed and M. Manoharan. All rights reserved. A Mathematical Model for Fuzzy -Median Problem with Fuzzy Weights and Variables Sun, 10 Apr 2016 08:07:02 +0000 We investigate the -median problem with fuzzy variables and weights of vertices. The fuzzy equalities and inequalities transform to crisp cases by using some technique used in fuzzy linear programming. We show that the fuzzy objective function also can be replaced by crisp functions. Therefore an auxiliary linear programming model is obtained for the fuzzy -median problem. The results are compared with two previously proposed methods. Fatemeh Taleshian and Jafar Fathali Copyright © 2016 Fatemeh Taleshian and Jafar Fathali. All rights reserved. Continuous Time Dynamic Contraflow Models and Algorithms Mon, 28 Mar 2016 12:07:12 +0000 The research on evacuation planning problem is promoted by the very challenging emergency issues due to large scale natural or man-created disasters. It is the process of shifting the maximum number of evacuees from the disastrous areas to the safe destinations as quickly and efficiently as possible. Contraflow is a widely accepted model for good solution of evacuation planning problem. It increases the outbound road capacity by reversing the direction of roads towards the safe destination. The continuous dynamic contraflow problem sends the maximum number of flow as a flow rate from the source to the sink in every moment of time unit. We propose the mathematical model for the continuous dynamic contraflow problem. We present efficient algorithms to solve the maximum continuous dynamic contraflow and quickest continuous contraflow problems on single source single sink arbitrary networks and continuous earliest arrival contraflow problem on single source single sink series-parallel networks with undefined supply and demand. We also introduce an approximation solution for continuous earliest arrival contraflow problem on two-terminal arbitrary networks. Urmila Pyakurel and Tanka Nath Dhamala Copyright © 2016 Urmila Pyakurel and Tanka Nath Dhamala. All rights reserved. Phase-Type Arrivals and Impatient Customers in Multiserver Queue with Multiple Working Vacations Tue, 15 Mar 2016 13:36:14 +0000 We consider a PH/M/c queue with multiple working vacations where the customers waiting in queue for service are impatient. The working vacation policy is the one in which the servers serve at a lower rate during the vacation period rather than completely ceasing the service. Customer’s impatience is due to its arrival during the period where all the servers are in working vacations and the arriving customer has to join the queue. We formulate the system as a nonhomogeneous quasi-birth-death process and use finite truncation method to find the stationary probability vector. Various performance measures like the average number of busy servers in the system during a vacation as well as during a nonvacation period, server availability, blocking probability, and average number of lost customers are given. Numerical examples are provided to illustrate the effects of various parameters and interarrival distributions on system performance. Cosmika Goswami and N. Selvaraju Copyright © 2016 Cosmika Goswami and N. Selvaraju. All rights reserved. Usage of Cholesky Decomposition in order to Decrease the Nonlinear Complexities of Some Nonlinear and Diversification Models and Present a Model in Framework of Mean-Semivariance for Portfolio Performance Evaluation Tue, 15 Mar 2016 12:38:59 +0000 In order to get efficiency frontier and performance evaluation of portfolio, nonlinear models and DEA nonlinear (diversification) models are mostly used. One of the most fundamental problems of usage of nonlinear and diversification models is their computational complexity. Therefore, in this paper, a method is presented in order to decrease nonlinear complexities and simplify calculations of nonlinear and diversification models used from variance and covariance matrix. For this purpose, we use a linear transformation which is obtained from the Cholesky decomposition of covariance matrix and eliminate linear correlation among financial assets. In the following, variance is an appropriate criterion for the risk when distribution of stock returns is to be normal and symmetric as such a thing does not occur in reality. On the other hand, investors of the financial markets do not have an equal reaction to positive and negative exchanges of the stocks and show more desirability towards the positive exchanges and higher sensitivity to the negative exchanges. Therefore, we present a diversification model in the mean-semivariance framework which is based on the desirability or sensitivity of investor to positive and negative exchanges, and rate of this desirability or sensitivity can be controlled by use of a coefficient. H. Siaby-Serajehlo, M. Rostamy-Malkhalifeh, F. Hosseinzadeh Lotfi, and M. H. Behzadi Copyright © 2016 H. Siaby-Serajehlo et al. All rights reserved. A Stochastic Location-Allocation Model for Specialized Services in a Multihospital System Wed, 24 Feb 2016 13:30:51 +0000 Rising costs, increasing demand, wasteful spending, and limited resources in the healthcare industry lead to an increasing pressure on hospital administrators to become as efficient as possible in all aspects of their operations including location-allocation. Some promising strategies for tackling these challenges are joining some hospitals to form multihospital systems (MHSs), specialization, and using the benefits of pooling resources. We develop a stochastic optimization model to determine the number, capacity, and location of hospitals in a MHS offering specialized services while they leverage benefits of pooling resources. The model minimizes the total cost borne by the MHS and its patients and incorporates patient service level, patient retention rates, and type of demand. Some computational analyses are carried out to gauge the benefits of optimally sharing resources for delivering specialized services across a subset of hospitals in the MHS against complete decentralization (CD) and full centralization (FC) policies. Khadijeh Naboureh and Ehram Safari Copyright © 2016 Khadijeh Naboureh and Ehram Safari. All rights reserved. Aircraft Scheduled Airframe Maintenance and Downtime Integrated Cost Model Tue, 23 Feb 2016 13:18:26 +0000 Aviation industry has grown rapidly since the first scheduled commercial aviation started one hundred years ago. There is a fast growth in the number of passengers, routes, and frequencies, with high revenues and low margins, which make this industry one of the most challenging businesses in the world. Every operator aims to undertake the minimum operating cost and gain profit as much as possible. One of the significant elements of operator’s operating cost is the maintenance cost. During maintenance scheduling, operator calculates the maintenance cost that it needs to budget. Previous works show that this calculation includes only costs that are directly related to the maintenance process such as cost of labor, material, and equipment. In some cases, overhead cost is also included. Some of previous works also discuss the existence of another cost throughout aircraft downtime, which is defined as cost of revenue loss. Nevertheless, there is not any standard model that shows how to define and calculate downtime cost. For that reason, the purpose of this paper is to introduce a new model and analysis technique that can be used to calculate aircraft downtime cost due to maintenance. Remzi Saltoğlu, Nazmia Humaira, and Gökhan İnalhan Copyright © 2016 Remzi Saltoğlu et al. 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.