An empirical test of the gravity p-median model

A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

Distance measure and the p-median problem in rural areas

The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

Network density and the p-median solution

The p-medianmodel is commonly used to find optimal locations of facilities for geographically distributed demands. So far, there are few studies that have considered the importance of the road network in the model. However, Han, Håkansson, and Rebreyend (2013) examined the solutions of the p-median model with densities of the road network varying from 500 to 70,000 nodes. They found as the density went beyond some 10,000 nodes, solutions have no further improvements but gradually worsen. The aim of this study is to check their findings by using an alternative heuristic being vertex substitution, as a complement to their using simulated annealing. We reject the findings in Han et al (2013). The solutions do not further improve as the nodes exceed 10,000, but neither do the solutions deteriorate.

A computational comparison of different algorithms for very large p-median problems

In this paper, we propose a new method for solving large scale p-median problem instances based on real data. We compare different approaches in terms of runtime, memory footprint and quality of solutions obtained. In order to test the different methods on real data, we introduce a new benchmark for the p-median problem based on real Swedish data. Because of the size of the problem addressed, up to 1938 candidate nodes, a number of algorithms, both exact and heuristic, are considered. We also propose an improved hybrid version of a genetic algorithm called impGA. Experiments show that impGA behaves as well as other methods for the standard set of medium-size problems taken from Beasley’s benchmark, but produces comparatively good results in terms of quality, runtime and memory footprint on our specific benchmark based on real Swedish data.

Testing the gravity p-median model empirically

Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

Median Household Income in Maine by Census Tract

http://digitalcommons.colby.edu/atlasofmaine2008/1015/thumbnail.jpg

Preparation of nanofibre yarns from electrospun nonwoven strips

From ancient to modern time, humans have been trying to use finer fibres to make fibrous products for various purposes and believing that finer fibres have better aesthetic qualities. So far, the commercial fibres have been reduced to microns in diameter, but it seems difficult to further reduce the fibre fineness to submicrons using conventional fibre-making techniques.
Electrospinning is a promising technique to produce continuous fibres with diameters on nanometre scales. This technique involves stretching a polymer fluid under a strong electric field into fine filaments, which are deposited randomly on the electrode collector forming a nonwoven nanofibre mat in most cases. Despite considerable efforts in exploring the applications of electrospun nanofibres in non-fibrous fields [1], very limited work has been conducted on using this material to process mechanically robust nanofibre yarns [2,3].

Should capillary blood glucose measurements be used in population surveys?

Objective
To determine the accuracy and appropriateness of capillary blood glucose testing in population surveys.
Materials and methods
Capillary blood glucose using the Rochec ACCU-CHEK instrument and Advantage 11 Test Strips was compared to a laboratory instrument. Three independent cross-sectional risk factor surveys (n=1432) and baseline individuals from the Greater Green Triangle Diabetes Prevention Project (n=341) provided both fasting plasma and capillary blood glucose measurements. Accuracy of capillary glucoses was assessed using the ISO 15197 standard. The median age of the participants was 71years, ranging from 25 to 84years. There were 799 males and 974 females.
Results
Capillary glucose method had poorer precision at lower concentrations (CV: 9.50%, mean=3.09mmol/L, CV: 4.90%, mean=16.78mmol/L, n=233 replicates). Individual discrepancies were seen across the measuring range (2.8–19.9mmol/L, n=1773). In total, 94.5% of results fell within the minimum acceptable accuracy standards. This was slightly short of the 95% of results required to meet the ISO 15197 standard. The prevalence of diabetes in the study population using glucose 7.0mmol/L was 2.4% (95%CI 1.8–3.3%) according to fasting plasma glucose and 2.8% (2.1–3.8%) according to fasting capillary glucose. The lower WHO-defined cut-off of 6.1mmol/L for capillary blood glucose testing gave a prevalence of 10.7% (9.0–12.5%).
Conclusions
This study of matched capillary and plasma glucose results concludes that while it is appropriate to use fasting capillary glucose levels to determine the prevalence of diabetes in populations, it should not be used to reliably diagnose diabetes in individuals.

The median and its extensions

We review various representations of the median and related aggregation functions. An advantage of the median is that it discards extreme values of the inputs, and hence exhibits a better central tendency than the arithmetic mean. However, the value of the median depends on only one or two central inputs. Our aim is to design median-like aggregation functions whose value depends on several central inputs. Such functions will preserve the stability of the median against extreme values, but will take more inputs into account. A method based on graduation curves is presented.

Aggregation for Atanassov's intuitionistic and interval valued fuzzy sets: the median operator

Atanassov's intuitionistic fuzzy sets (AIFS) and interval valued fuzzy sets (IVFS) are two generalizations of a fuzzy set, which are equivalent mathematically although different semantically. We analyze the median aggregation operator for AIFS and IVFS. Different mathematical theories have lead to different definitions of the median operator. We look at the median from various perspectives: as an instance of the intuitionistic ordered weighted averaging operator, as a Fermat point in a plane, as a minimizer of input disagreement, and as an operation on distributive lattices. We underline several connections between these approaches and summarize essential properties of the median in different representations.

Upgrading arc median shortest path problem for an urban transportation network

In this paper, we propose an algorithm for an upgrading arc median shortest path problem for a transportation network. The problem is to identify a set of nondominated paths that minimizes both upgrading cost and overall travel time of the entire network. These two objectives are realistic for transportation network problems, but of a conflicting and noncompensatory nature. In addition, unlike upgrading cost which is the sum of the arc costs on the path, overall travel time of the entire network cannot be expressed as a sum of arc travel times on the path. The proposed solution approach to the problem is based on heuristic labeling and exhaustive search techniques, in criteria space and solution space, respectively. The first approach labels each node in terms of upgrading cost, and deletes cyclic and infeasible paths in criteria space. The latter calculates the overall travel time of the entire network for each feasible path, deletes dominated paths on the basis of the objective vector and identifies a set of Pareto optimal paths in the solution space. The computational study, using two small-scale transportation networks, has demonstrated that the algorithm proposed herein is able to efficiently identify a set of nondominated median shortest paths, based on two conflicting and noncompensatory objectives.

Solving the median shortest path problem in the planning and design of urban transportation networks using a vector labeling algorithm

This paper proposes an alternative algorithm to solve the median shortest path problem (MSPP) in the planning and design of urban transportation networks. The proposed vector labeling algorithm is based on the labeling of each node in terms of a multiple and conflicting vector of objectives which deletes cyclic, infeasible and extreme-dominated paths in the criteria space imposing cyclic break (CB), path cost constraint (PCC) and access cost parameter (ACP) respectively. The output of the algorithm is a set of Pareto optimal paths (POP) with an objective vector from predetermined origin to destination nodes. Thus, this paper formulates an algorithm to identify a non-inferior solution set of POP based on a non-dominated set of objective vectors that leaves the ultimate decision to decision-makers. A numerical experiment is conducted using an artificial transportation network in order to validate and compare results. Sensitivity analysis has shown that the proposed algorithm is more efficient and advantageous over existing solutions in terms of computing execution time and memory space used.

An algorithm to median shortest path problem (MSPP) in the design of urban transportation networks

This paper proposes an efficient solution algorithm for realistic multi-objective median shortest path problems in the design of urban transportation networks. The proposed problem formulation and solution algorithm to median shortest path problem is based on three realistic objectives via route cost or investment cost, overall travel time of the entire network and total toll revenue. The proposed solution approach to the problem is based on the heuristic labeling and exhaustive search technique in criteria space and solution space of the algorithm respectively. The first labels each node in terms of route cost and deletes cyclic and infeasible paths in criteria space imposing cyclic break and route cost constraint respectively. The latter deletes dominated paths in terms of objectives vector in solution space in order to identify a set of Pareto optimal paths. The approach, thus, proposes a non-inferior solution set of Pareto optimal paths based on non-dominated objective vector and leaves the ultimate decision to decision-makers for purpose specific final decision during applications. A numerical experiment is conducted to test the proposed algorithm using artificial transportation network. Sensitivity analyses have shown that the proposed algorithm is advantageous and efficient over existing algorithms to find a set of Pareto optimal paths to median shortest paths problems.

Serotonergic neurons in the median raphe nucleus regulate inhibitory avoidance but not escape behavior in the rat elevated T-maze test of anxiety

Rationale: A wealth of evidence supports the involvement of the serotonergic neurons of the median raphe nucleus (MRN) in anxiety. However, it is presently unclear whether serotonergic pathways arising from this nucleus play distinguishing regulatory roles in defensive behaviors that have been associated with specific subtypes of anxiety disorders. Objectives: To evaluate the role of the MRN serotonergic neurons in the regulation of two defensive behaviors, inhibitory avoidance and escape, which have been related, respectively, to generalized anxiety and panic disorders. Methods: Male Wistar rats were submitted to the elevated T-maze test of anxiety after intra-MRN administration of drugs that either non-selectively or selectively change the activity of the serotonergic neurons. Results: Intra-MRN injection of FG 7142 (0.04 and 0.08 nmol) and kainic acid (0.03 and 0.06 nmol), drugs that non-selectively stimulate the MRN serotonergic neurons, facilitated inhibitory avoidance acquisition, but impaired escape performance. Microinjection of muscimol (0.11 and 0.22 nmol), a compound that non-selectively inhibits the activity of the MRN serotonergic neurons, impaired inhibitory avoidance and facilitated escape performance. Both kainic acid and muscimol also changed rat locomotion in the open-field test. Intra-MRN injection of 8-OH-DPAT (0.6-15 nmol) and WAY-100635 (0.18-0.74 nmol), respectively an agonist and an antagonist of somatodendritic 5-HT1A receptors located on serotonergic neurons of the MRN, only affected inhibitory avoidance-while the former inhibited the acquisition of this behavior, the latter facilitated it. Conclusion: MRN serotonergic neurons seem to be selectively involved in the regulation of inhibitory avoidance in the elevated T-maze. This result supports the proposal that 5-HT pathways departing from this nucleus play an important role in anxiety processing, with implications for pathologies such as generalized anxiety disorder.