Speeding up the optimal method of Drezner for the p-centre problem in the plane

This paper revisits an early but interesting optimal algorithm first proposed by Drezner to solve the continuous p-centre problem. The original algorithm is reexamined and efficient neighbourhood reductions which are mathematically supported are proposed to improve its overall computational performance. The revised algorithm yields a considerably high reduction in computational time reaching, in some cases, a decrease of 96%. This new algorithm is now able to find proven optimal solutions for large data sets with over 1300 demand points and various values of p for the first time

Optimal solutions for the continuous p-centre problem and related α-neighbour and conditional problems: A relaxation-based algorithm

This paper aims to solve large continuous p-centre problems optimally by re-examining a recent relaxation-based algorithm. The algorithm is strengthened by adding four mathematically supported enhancements to improve its efficiency. This revised relaxation algorithm yields a massive reduction in computational time enabling for the first time larger data-sets to be solved optimally (e.g., up to 1323 nodes). The enhanced algorithm is also shown to be flexible as it can be easily adapted to optimally solve related practical location problems that are frequently faced by senior management when making strategic decisions. These include the α-neighbour p-centre problem and the conditional p-centre problem. A scenario analysis using variable α is also performed to provide further managerial insights

The Grizzly, September 13, 2001

Eating in Wismer: The Crunch at Lunch • America. No Longer the Beautiful • Collegeville Police Crack Down on Ursinus Students • A New Look and New Menu at Wismer • Service Woes for Select Residents • Opinions: Wismer Bussing: A Major Problem; New Social Host Policy a Wet Blanket • International Film Festival Brings Foreign Flair to Ursinus College Campus • Review of the Restaurant La Fontana • Unconventional Fringe Fest Takes Over Philly • Like Old Movies? Then the Colonial Theater is the Place to Be • Pizza: Where\u27s the Best Buy for Your Money? • Ursinus Webpage is Getting a Makeover • Colonization of Sigma Sigma Sigma • Duncan Breaks Record as Ursinus Downs Waynesburg • Cross Country Breezes Through LBV Invitational • Two Tough Teams Equal First Two Losses for Men\u27s Soccer • UC Women\u27s Volleyball Defeats Wilkes for Third Win • Bears Fall to Montclair; Tie with Widener • UC Field Hockey Takes Slap Shot • Soccer Teams Without a Home Fieldhttps://digitalcommons.ursinus.edu/grizzlynews/1493/thumbnail.jp

The Grizzly, January 24, 2002

Ursinus has Spoken: Results of the Grizzly Survey • A Tribute to Dr. Martin Luther King Jr. • Ursinus Joins the War Against Bioterrorism • Limerick Nuclear Plant Cited for Safety Violation • New Housing for Spring Semester • Laptop Initiative • Opinions: Laptop Controversy; Are the Crowds too Much for Wismer to Handle?; En Espana: One Student\u27s Experience Abroad • Ursinus and MTV: A Winning Combination • Judy Chicago on Display at Berman • Sigma Sigma Sigma to Install Newest Collegiate Chapter at Ursinus • To be Educated or not to be? • Ursinus Swimmers Reap Benefits of a Trip Down South Showing Well Against York • Bouncing into Another Season with the Gymnastics Team • Ursinus Wrestling: A Conference Powerhouse in the Making • Indoor Track Teams Place 4th and 7th at Gulden Relays • Swarthmore Proves to be too Much for our Lady Bearshttps://digitalcommons.ursinus.edu/grizzlynews/1504/thumbnail.jp

Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome.

How does human brain structure mature during adolescence? We used MRI to measure cortical thickness and intracortical myelination in 297 population volunteers aged 14-24 y old. We found and replicated that association cortical areas were thicker and less myelinated than primary cortical areas at 14 y. However, association cortex had faster rates of shrinkage and myelination over the course of adolescence. Age-related increases in cortical myelination were maximized approximately at the internal layer of projection neurons. Adolescent cortical myelination and shrinkage were coupled and specifically associated with a dorsoventrally patterned gene expression profile enriched for synaptic, oligodendroglial- and schizophrenia-related genes. Topologically efficient and biologically expensive hubs of the brain anatomical network had greater rates of shrinkage/myelination and were associated with overexpression of the same transcriptional profile as cortical consolidation. We conclude that normative human brain maturation involves a genetically patterned process of consolidating anatomical network hubs. We argue that developmental variation of this consolidation process may be relevant both to normal cognitive and behavioral changes and the high incidence of schizophrenia during human brain adolescence.This study was supported by the Neuroscience in Psychiatry Network, a strategic award by the Wellcome Trust to the University of Cambridge and University College London. Additional support was provided by the NIHR Cambridge Biomedical Research Centre and the MRC/Wellcome Trust Behavioural & Clinical Neuroscience Institute. PEV is supported by the MRC (MR/K020706/1). We used the Darwin Supercomputer of the University of Cambridge High Performance Computing Service provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council.This is the author accepted manuscript. This is the author accepted manuscript. The final version is available from the National Academy of Sciences via https://doi.org/10.1073/pnas.160174511

The Grizzly, November 1, 2001

Students Join Together to Take Back the Night • World-Renowned Composer, Arranger and Educator will Unite the Ursinus Campus in Song this Weekend • Ursinus Students Celebrate the Haunting Holiday with Local Children • Understanding Biological Terrorism • UC Groups Clean up the Environment • Professor Valerie Martinez Named a Commonwealth Speaker • Opinions: Community Service for all Campus Organizations?; Your Patriotic Duty: Voting Guarantees Your Freedom; Inspirational Take Back the Night • Faustus a Devilishly Good Play • Cost of the Midnight Munchies • RHA Sponsors Spades Tournament • Farewell Game Leaves Bears Women\u27s Soccer Kicked by Mules •XC Digs in at Centennial Conference Meet • Dale Named Centennial Conference Player of the Week • Duncan Becomes All-time Leader in Rush • Volleyball Downed by G-M • Bears Brush Away Colgate • Muhlenberg Strikes Yet Again • Bears Football Kicked by Muhlenberg\u27s Mules, 23-20https://digitalcommons.ursinus.edu/grizzlynews/1499/thumbnail.jp

An Adaptive Perturbation-Based Heuristic: An Application to the Continuous p-Centre Problem

A self-adaptive heuristic that incorporates a variable level of perturbation, a novel local search and a learning mechanism is proposed to solve the p-centre problem in the continuous space. Empirical results, using several large TSP-Lib data sets, some with over 1300 customers with various values of p, show that our proposed heuristic is both effective and efficient. This perturbation metaheuristic compares favourably against the optimal method on small size instances. For larger instances the algorithm outperforms both a multi-start heuristic and a discrete-based optimal approach while performing well against a recent powerful VNS approach. This is a self-adaptive method that can easily be adopted to tackle other combinatorial/global optimisation problems. For benchmarking purposes, the medium size instances with nodes are solved optimally for the first time, though requiring a large amount of computational time. As a by-product of this research, we also report for the first time the optimal solution of the vertex p-centre problem for these TSP-Lib data sets

Drezner's exact method for the continuous p-centre problem revisited

Drezner's optimal algorithm for the p-centre problem is an elegant but somewhat slow method. We suggest some technical enhancements that significantly improve the method's efficiency