Many solution techniques for discrete location-allocation problems make use of a sorted distance strings data structure in order to speed processing time. The primary drawback to distance strings is that in a standard computer architecture they require approximately 50% additional memory storage in comparison to a standard distance matrix. To reduce the additional memory requirements of distance strings, researchers such as Hillsman [1980] and Densham and Rushton [1992a] have proposed a strategy for cutting the distance strings to include only sets of relatively close neighbor nodes. This has become an important implementation issue for solving relatively large location- allocation problems. In fact, the new Location-Allocation module of the ARC/Info GIS system uses a distance string structure and a string cutoff option to save storage and processing time. The danger in employing only partial distance strings is that if too few distance entries are stored in the distance strings, heuristic or algorithmic performance may be compromised in that the quality of the solutions generated may be less than desirable. This paper tests the effects on solution quality of imposing different distance string definitions and sizes. The goal is to establish guidelines concerning the degree to which the distance strings data structure may be reduced for memory savings without adversely affecting solution quality. The paper proposes and compares two alternative methods to that of Hillsman and of Densham and Rushton for the selection of nodes to be included within the distance strings data structure. We show that the two new alternative methods for defining distance strings appear to outperform the earlier approach. The results of this paper can be used to aid users in determining the extent that distance string cutoffs should be employed in application as well as aid in the development of location modeling software.

There has been considerable interest in the development of analysis techniques for Geographical Information Systems (GIS). This includes such normative spatial models as vehicle routing models, districting and turfing models for dividing up land into territories for schools, sales/service, and voting, and location models for identifying sites or patterns of sites to provide service accessibility. The GIS system may provide a unique data base for application and analysis. This paper discusses several problems associated with the integration of a normative location model into a GIS. A number of specifics associated with the p-median model are given. These include: demand zone definition, facility site definition, and solution algorithm selection and development. Within the context of selecting a solution process, we show that such a selection is not necessarily an easy one to make. We demonstrate that the best such solution technique may have some potential drawbacks in application. We present the results of several test applications and a glimpse of the pathology of the final solutions. This discussion raises a major, but often ignored, issue involving the application of a location heuristic: namely, how often should we restart a heuristic to help ensure that the best solution found is optimal or near-optimal. We propose and test a dynamic stopping rule that can be used to help ensure that the best solution is identified. The results of this analysis can be of great, practical value in the successful application of location models within a GIS framework.

In this review, we examine the current theoretical and experimental status of the chiral magnetic effect. We discuss possible future strategies for resolving uncertainties in interpretation including recommendations for theoretical work, recommendations for measurements based on data collected in the past five years, and recommendations for beam use in the coming years of RHIC. We specifically investigate the case for colliding nuclear isobars (nuclei with the same mass but different charge) and find the case compelling. We recommend that a program of nuclear isobar collisions to isolate the chiral magnetic effect from background sources be placed as a high priority item in the strategy for completing the RHIC mission.

The chiral magnetic effect (CME) is a novel transport phenomenon, arising from the interplay between quantum anomalies and strong magnetic fields in chiral systems. In high-energy nuclear collisions, the CME may survive the expansion of the quark-gluon plasma fireball and be detected in experiments. Over the past two decades, experimental searches for the CME have attracted extensive interest at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). The main goal of this study is to investigate three pertinent experimental approaches: the correlator, the R correlator, and the signed balance functions. We exploit simple Monte Carlo simulations and a realistic event generator (EBE-AVFD) to verify the equivalence of the core components among these methods and to ascertain their sensitivities to the CME signal and the background contributions for the isobar collisions at the RHIC.