G Rushton
Biographic Data
| ID | 3711390 |
|---|---|
| NAME | G Rushton |
| GIVEN NAMES | G |
| FAMILY NAME | Rushton |
| SIGNATURE | RUSHTON G |
| AFFILIATIONS | San Diego State University |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 27 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1966 |
| LATEST PUBLICATION YEAR | 1992 |
| H-INDEX | 3 |
Strategies for Solving Large Location-Allocation Problems by Heuristic Methods
Solution techniques for location-allocation problems usually are not a part of microcomputer-based geoprocessing systems because of the large volumes of data to process and store and the complexity of algorithms. In this paper, it is shown that processing costs for the most accurate, heuristic, location-allocation algorithm can be drastically reduced by exploiting the spatial structure of location-allocation problems. The strategies used, preproc…
The Effect of Distance Metric on the Degree of Spatial Competition between Firms
The proportion of a firm's market-area that is within a given, small, proportional difference in delivered-price between itself and its principal competitor, is an important measure of spatial competition. It is shown that for regular triangular and irregular spatial patterns of firms, areas of intense spatial competition are larger when transport costs are proportional to euclidean distances rather than to block distances, but this is not true f…
Revealed Space Preference Theory — A Rejoinder
Some Spatial Characteristics of Iowa's Dispersed Farm Population and Their Implications for the Grouping of Central Place Functions
(1966). Some Spatial Characteristics of Iowa's Dispersed Farm Population and Their Implications for the Grouping of Central Place Functions. Economic Geography: Vol. 42, No. 3, pp. 261-272
Some Spatial Characteristics of Iowa's Dispersed Farm Population and Their Implications for the Grouping of Central Place Functions
(1966). Some Spatial Characteristics of Iowa's Dispersed Farm Population and Their Implications for the Grouping of Central Place Functions. Economic Geography: Vol. 42, No. 3, pp. 261-272
Strategies for Solving Large Location-Allocation Problems by Heuristic Methods
Solution techniques for location-allocation problems usually are not a part of microcomputer-based geoprocessing systems because of the large volumes of data to process and store and the complexity of algorithms. In this paper, it is shown that processing costs for the most accurate, heuristic, location-allocation algorithm can be drastically reduced by exploiting the spatial structure of location-allocation problems. The strategies used, preproc…
Revealed Space Preference Theory — A Rejoinder
The Effect of Distance Metric on the Degree of Spatial Competition between Firms
The proportion of a firm's market-area that is within a given, small, proportional difference in delivered-price between itself and its principal competitor, is an important measure of spatial competition. It is shown that for regular triangular and irregular spatial patterns of firms, areas of intense spatial competition are larger when transport costs are proportional to euclidean distances rather than to block distances, but this is not true f…
Some Spatial Characteristics of Iowa's Dispersed Farm Population and Their Implications for the Grouping of Central Place Functions
(1966). Some Spatial Characteristics of Iowa's Dispersed Farm Population and Their Implications for the Grouping of Central Place Functions. Economic Geography: Vol. 42, No. 3, pp. 261-272
Revealed Space Preference Theory — A Rejoinder
The Effect of Distance Metric on the Degree of Spatial Competition between Firms
The proportion of a firm's market-area that is within a given, small, proportional difference in delivered-price between itself and its principal competitor, is an important measure of spatial competition. It is shown that for regular triangular and irregular spatial patterns of firms, areas of intense spatial competition are larger when transport costs are proportional to euclidean distances rather than to block distances, but this is not true f…
Strategies for Solving Large Location-Allocation Problems by Heuristic Methods
Solution techniques for location-allocation problems usually are not a part of microcomputer-based geoprocessing systems because of the large volumes of data to process and store and the complexity of algorithms. In this paper, it is shown that processing costs for the most accurate, heuristic, location-allocation algorithm can be drastically reduced by exploiting the spatial structure of location-allocation problems. The strategies used, preproc…
Mathematics (3 works) · Computer Science (2 works) · Sociology (2 works) · Statistics (2 works) · Agricultural Economics and Policy (1 work) · Architecture (1 work) · Architecture (1 work) · Artificial Intelligence (1 work) · Business Strategy and Innovation (1 work) · Central city (1 work)