2,581 research outputs found

    Implementing TURF analysis through binary linear programming

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    This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.Total Unduplicated Reach and Frequency; Market research; Competitive algorithm; Product optimization; Large datasets

    Location models for airline hubs behaving as M/D/c queues

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    Models are presented for the optimal location of hubs in airline networks, that take into consideration the congestion effects. Hubs, which are the most congested airports, are modeled as M/D/c queuing systems, that is, Poisson arrivals, deterministic service time, and {\em c} servers. A formula is derived for the probability of a number of customers in the system, which is later used to propose a probabilistic constraint. This constraint limits the probability of {\em b} airplanes in queue, to be lesser than a value α\alpha. Due to the computational complexity of the formulation. The model is solved using a meta-heuristic based on tabu search. Computational experience is presented.Hub location, congestion, tabu-search

    Consumer choice in competitive location models: Formulations and heuristics

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    A new direction of research in Competitive Location theory incorporates theories of Consumer Choice Behavior in its models. Following this direction, this paper studies the importance of consumer behavior with respect to distance or transportation costs in the optimality of locations obtained by traditional Competitive Location models. To do this, it considers different ways of defining a key parameter in the basic Maximum Capture model (MAXCAP). This parameter will reflect various ways of taking into account distance based on several Consumer Choice Behavior theories. The optimal locations and the deviation in demand captured when the optimal locations of the other models are used instead of the true ones, are computed for each model. A metaheuristic based on GRASP and Tabu search procedure is presented to solve all the models. Computational experience and an application to 55-node network are also presented.Distance, competitive location models, consumer choice behavior, GRASP, tabu

    Another experimental look at reciprocal behavior: indirect reciprocity

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    This paper highlights a new social motivation, the indirect reciprocity, through a three-player dictator-ultimatum game. Player 2 has the opportunity to reward or punish indirectly the player 1 by inciting – with her offer - player 3 to accept or to reject the division. We implement three treatments: in the first two we vary player 2’s available information whereas in treatment 3, players take part in a dictator game - as proposers - before being player 2s in the dictator-ultimatum game. Results show that 55% of subjects in treatment 2 and 28% in treatment 3 behave as indirect reciprocity predicts. Another reciprocal behavior - the generalized reciprocity - is investigated through a three-player dictator game. Our data show that 80% of players 2 act according to this reciprocal behavior. Finally, our findings confirm that the more complex the strategic interaction becomes the more self-regarding behavior is likely and the less other-regarding behaviors, such as reciprocity, dominate.indirect reciprocity; generalized reciprocity; dictator game; ultimatum game; individual behavior

    Median problems in networks

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    The P-median problem is a classical location model “par excellence”. In this paper we, first examine the early origins of the problem, formulated independently by Louis Hakimi and Charles ReVelle, two of the fathers of the burgeoning multidisciplinary field of research known today as Facility Location Theory and Modelling. We then examine some of the traditional heuristic and exact methods developed to solve the problem. In the third section we analyze the impact of the model in the field. We end the paper by proposing new lines of research related to such a classical problem.P-median, location modelling

    Probabilistic maximal covering location-allocation models with constrained waiting time or queue length for congested systems

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    When dealing with the design of service networks, such as health and EMS services, banking or distributed ticket selling services, the location of service centers has a strong influence on the congestion at each of them, and consequently, on the quality of service. In this paper, several models are presented to consider service congestion. The first model addresses the issue of the location of the least number of single--server centers such that all the population is served within a standard distance, and nobody stands in line for a time longer than a given time--limit, or with more than a predetermined number of other clients. We then formulate several maximal coverage models, with one or more servers per service center. A new heuristic is developed to solve the models and tested in a 30--nodes network.Discrete facility location, queuing, emergency services location

    Location models in the public sector

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    The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.Location analysis, public facilities, covering models

    Another experimental look at reciprocal behavior: indirect reciprocity

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    This paper highlights a new social motivation, the indirect reciprocity, through a three-player dictator-ultimatum game. Player 2 has the opportunity to reward or punish indirectly the player 1 by inciting – with her offer - player 3 to accept or to reject the division. We implement three treatments: in the first two we vary player 2’s available information whereas in treatment 3, players take part in a dictator game - as proposers - before being player 2s in the dictatorultimatum game. Results show that 55% of subjects in treatment 2 and 28% in treatment 3 behave as indirect reciprocity predicts. Another reciprocal behavior - the generalized reciprocity - is investigated through a three-player dictator game. Our data show that 80% of players 2 act according to this reciprocal behavior. Finally, our findings confirm that the more complex the strategic interaction becomes the more self-regarding behavior is likely and the less otherregarding behaviors, such as reciprocity, dominate.

    Incorporating waiting time in competitive location models: Formulations and heuristics

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    In this paper we propose a metaheuristic to solve a new version of the Maximum Capture Problem. In the original MCP, market capture is obtained by lower traveling distances or lower traveling time, in this new version not only the traveling time but also the waiting time will affect the market share. This problem is hard to solve using standard optimization techniques. Metaheuristics are shown to offer accurate results within acceptable computing times.Market capture, queuing, ant colony optimization

    Locating emergency services with priority rules: The priority queuing covering location problem

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    One of the assumptions of the Capacitated Facility Location Problem (CFLP) is that demand is known and fixed. Most often, this is not the case when managers take some strategic decisions such as locating facilities and assigning demand points to those facilities. In this paper we consider demand as stochastic and we model each of the facilities as an independent queue. Stochastic models of manufacturing systems and deterministic location models are put together in order to obtain a formula for the backlogging probability at a potential facility location. Several solution techniques have been proposed to solve the CFLP. One of the most recently proposed heuristics, a Reactive Greedy Adaptive Search Procedure, is implemented in order to solve the model formulated. We present some computational experiments in order to evaluate the heuristics’ performance and to illustrate the use of this new formulation for the CFLP. The paper finishes with a simple simulation exercise.Location, queuing, greedy heuristics, simulation
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