Abstract: Consider the problem faced by a purchaser of solid waste management services, who needs to identify waste collection points, the assignment of waste generation points to waste collection points, and the type and number of receptacles utilized at each collection point. Receptacles whose collection schedule is specified in advance are charged a fixed fee according to the number of times the receptacle is serviced (emptied) per week. For other receptacles, the purchaser pays a fee comprised of a fixed service charge, plus a variable cost that is assessed on a per-ton-removed basis. We develop a mathematical programming model to minimize the costs that the purchaser pays to the waste management provider, subject to a level of service that is sufficient to collect all of the purchaser’s required waste. Examining historical data from the University of Missouri, we observed significant variability in the amount of waste serviced for nonscheduled receptacles. Because this variability has a significant impact on cost, we modified our model using robust optimization techniques to address the observed uncertainty. Our model’s highly robust solution, while slightly more expensive than the nonrobust solution in the most-optimistic scenario, significantly outperforms the nonrobust solution for all other potential scenarios. PubDate: Sun, 29 Jan 2017 00:00:00 +000

Abstract: In this paper, we study a project scheduling problem that is called resource constrained project scheduling problem under minimization of total weighted resource tardiness penalty cost (RCPSP-TWRTPC). In this problem, the project is subject to renewable resources, each renewable resource is available for limited time periods during the project life cycle, and keeping the resource for each extra period results in some tardiness penalty cost. We introduce a branch and bound algorithm to solve the problem exactly and use several bounding, fathoming, and dominance rules in our algorithm to shorten the enumeration process. We point out parameters affecting the RCPSP-TWRTPC degree of difficulty, generate extensive sets of sample instances for the problem, and perform comprehensive experimental analysis using the customized algorithm and also CPLEX solver. We analyze the algorithm behavior with respect to the changes in instances degree of difficulty and compare its performance for different cases with the CPLEX solver. The results reveal algorithm efficiency. PubDate: Tue, 10 Jan 2017 00:00:00 +000

Abstract: Data envelopment analysis (DEA) evaluates the efficiency of the transformation of a decision-making unit’s (DMU’s) inputs into its outputs. Finding the benchmarks of a DMU is one of the important purposes of DEA. The benchmarks of a DMU in DEA are obtained by solving some linear programming models. Currently, the obtained benchmarks are just found by using the information of the data of inputs and outputs without considering the decision-maker’s preferences. If the preferences of the decision-maker are available, it is very important to obtain the most preferred DMU as a benchmark of the under-assessment DMU. In this regard, we present an algorithm to find the most preferred DMU based on the utility function of decision-maker’s preferences by exploring some properties on that. The proposed method is constructed based on the projection of the gradient of the utility function on the production possibility set’s frontier. PubDate: Thu, 08 Dec 2016 09:41:42 +000

Abstract: Events such as natural disasters or combat operations require a rapid response capability from humanitarian service providers and military organizations. Such organizations can decrease their response times through the prepositioning of materiel in forward warehouses, reducing the time needed to transport items to the site of need. A particular challenge to the development of networks of prepositioning warehouses is that the warehouses themselves may be impacted by the very disruptions that drive demands for prepositioned materials. The objective of this research is to identify a reliable network posture, which is a set of utilized facility locations and an allocation of materiel to those locations, that can satisfy time-sensitive delivery requirements to potential locations around the globe, ensuring that demands can be satisfied even in the event of loss of access to a subset of storage sites (along with said sites’ materiel), all at minimum total cost. We develop new optimization formulations to account for differing levels of network reliability, all reflecting the time-sensitive environment faced by rapid response operations. We demonstrate an application of this methodology using rapid response material prepositioned by the US Air Force. PubDate: Wed, 05 Oct 2016 08:49:45 +000

Abstract: We introduce generalized subadditive generator functions for mixed integer linear programs. Our results extend Klabjan’s work from pure integer programs with nonnegative entries to general MILPs. These functions suffice to achieve strong subadditive duality. Several properties of the functions are shown. We then use this class of functions to generate certificates of optimality for MILPs. We have performed a computational test study on knapsack problems to investigate the efficiency of the certificates. PubDate: Wed, 31 Aug 2016 14:40:37 +000

Abstract: We consider a storage allocation model with a finite number of storage spaces. There are primary spaces and secondary spaces. All of them are numbered and ranked. Customers arrive according to a Poisson process and occupy a space for an exponentially distributed time period, and a new arrival takes the lowest ranked available space. We let and denote the numbers of occupied primary and secondary spaces and study the joint distribution in the steady state. The joint process behaves as a random walk in a lattice rectangle. We study the problem asymptotically as the Poisson arrival rate becomes large, and the storage capacities and are scaled to be commensurably large. We use a singular perturbation analysis to approximate the forward Kolmogorov equation(s) satisfied by the joint distribution. PubDate: Wed, 31 Aug 2016 13:34:37 +000

Abstract: Prey-predator algorithm (PPA) is a metaheuristic algorithm inspired by the interaction between a predator and its prey. In the algorithm, the worst performing solution, called the predator, works as an agent for exploration whereas the better performing solution, called the best prey, works as an agent for exploitation. In this paper, PPA is extended to a new version called nm-PPA by modifying the number of predators and also best preys. In nm-PPA, there will be n best preys and m predators. Increasing the value of n increases the exploitation and increasing the value of m increases the exploration property of the algorithm. Hence, it is possible to adjust the degree of exploration and exploitation as needed by adjusting the values of n and m. A guideline on setting parameter values will also be discussed along with a new way of measuring performance of an algorithm for multimodal problems. A simulation is also done to test the algorithm using well known eight benchmark problems of different properties and different dimensions ranging from two to twelve showing that nm-PPA is found to be effective in achieving multiple solutions in multimodal problems and also has better ability to overcome being trapped in local optimal solutions. PubDate: Tue, 26 Jul 2016 09:26:09 +000

Abstract: This study constructs a new travel risks’ evaluation model for freelancers to evaluate and select tour groups by considering the interdependencies of the evaluation criteria used. First of all, the proposed model adopts the Nominal Group Technique (NGT) to identify suitable evaluation criteria for evaluating travel risks. Six evaluation criteria and 18 subcriteria are obtained. The six evaluation criteria are financial risk, transportation risk, social risk, hygiene risk, sightseeing spot risk, and general risk for freelancer tour groups. Secondly, the model uses the analytic network process (ANP) to determine the relative weight of the criteria. Finally, examples of group package tours (GPTs) are used to demonstrate the travel risk evaluation process for this model. The results show that the Tokyo GPT is the best group tour. The proposed model helps freelancers to effectively evaluate travel risks and decision-making, making it highly applicable to academia and tour groups. PubDate: Sun, 10 Jul 2016 09:40:21 +000

Abstract: This paper presents a stock selection approach assisted by fuzzy procedures. In this approach, stocks are classified into groups according to business types. Within each group, the stocks are screened and then ranked according to their investment weight obtained from fuzzy quantitative analysis. Groups were also ranked according to their group weight obtained from fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to ideal solution method (TOPSIS). The overall weight for each stock was then derived from both of these weights and used for selecting a stock into the portfolio. As a demonstration, our analysis procedures were applied to a test set of data. PubDate: Tue, 05 Jul 2016 08:09:17 +000

Abstract: This paper deals with the stationary analysis of a fluid queue driven by an queueing model subject to Bernoulli-Schedule-Controlled Vacation and Vacation Interruption. The model under consideration can be viewed as a quasi-birth and death process. The governing system of differential difference equations is solved using matrix-geometric method in the Laplacian domain. The resulting solutions are then inverted to obtain an explicit expression for the joint steady state probabilities of the content of the buffer and the state of the background queueing model. Numerical illustrations are added to depict the convergence of the stationary buffer content distribution to one subject to suitable stability conditions. PubDate: Wed, 08 Jun 2016 06:24:14 +000

Abstract: An M/M/1 retrial queue with working vacation interruption is considered. Upon the arrival of a customer, if the server is busy, it would join the orbit of infinite size. The customers in the orbit will try for service one by one when the server is idle under the classical retrial policy with retrial rate , where is the size of the orbit. During a working vacation period, if there are customers in the system at a service completion instant, the vacation will be interrupted. Under the stable condition, the probability generating functions of the number of customers in the orbit are obtained. Various system performance measures are also developed. Finally, some numerical examples and cost optimization analysis are presented. PubDate: Mon, 30 May 2016 11:25:21 +000

Abstract: 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. PubDate: Thu, 19 May 2016 09:17:01 +000

Abstract: 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. PubDate: Wed, 27 Apr 2016 11:11:05 +000

Abstract: 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. PubDate: Sun, 10 Apr 2016 08:07:02 +000

Abstract: 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. PubDate: Mon, 28 Mar 2016 12:07:12 +000

Abstract: 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. PubDate: Tue, 15 Mar 2016 13:36:14 +000

Abstract: 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. PubDate: Tue, 15 Mar 2016 12:38:59 +000

Abstract: 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. PubDate: Wed, 24 Feb 2016 13:30:51 +000

Abstract: 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. PubDate: Tue, 23 Feb 2016 13:18:26 +000

Abstract: 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. PubDate: Wed, 20 Jan 2016 07:33:58 +000

Abstract: 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. PubDate: Sun, 10 Jan 2016 06:47:51 +000

Abstract: 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. PubDate: Sun, 29 Nov 2015 13:03:33 +000

Abstract: 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. PubDate: Thu, 08 Oct 2015 15:31:31 +000

Abstract: 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. PubDate: Sun, 04 Oct 2015 16:34:48 +000

Abstract: This paper proposes three numerical algorithms based on Karmarkar’s interior point technique for solvingnonlinear convex programming problems subject to linear constraints. The first algorithm uses the Karmarkaridea and linearization of the objective function. The second and third algorithms are modification ofthe first algorithm using the Schrijver and Malek-Naseri approaches, respectively. These three novel schemesare tested against the algorithm of Kebiche-Keraghel-Yassine (KKY). It is shown that these three novel algorithmsare more efficient and converge to the correct optimal solution, while the KKY algorithm fails insome cases. Numerical results are given to illustrate the performance of the proposed algorithms. PubDate: Wed, 16 Sep 2015 06:14:30 +000

Abstract: 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. PubDate: Mon, 22 Jun 2015 11:51:20 +000

Abstract: 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. PubDate: Mon, 30 Mar 2015 07:45:43 +000

Abstract: 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. PubDate: Thu, 19 Feb 2015 07:10:47 +000

Abstract: 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. PubDate: Tue, 10 Feb 2015 09:09:27 +000

Abstract: 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 onavailable information on incoming and outgoing passengers. Second, we employ the obtained information on passenger trafficto introduce a game-theoretic model of passenger traffic distribution with respect to transport facilities. PubDate: Tue, 03 Feb 2015 06:47:25 +000