A two-level genetic algorithm for the location-allocation problem with efficient capacity on servers
Tahereh Sayyar et al.
What the paper says
Purpose The main goal is to reconsider the number of servers to a specified value so that the sum of the traveling cost of every customer to servers, as well as the sum of the input costs relative to each server, is minimized. To this end, we propose a mathematical programming model and to solve the proposed model, we propose a two-level genetic algorithm. Design/methodology/approach In this article, we propose a novel allocation-location problem, considering the efficiency concept based on data envelopment analysis. In most location models, a predetermined capacity is associated with each server. In this article, we propose a new joint model in the efficiencies of the servers are considered as their capacities. Findings We apply our models in the transportation of high school's students in Shahrood city, who are faced with a low rate of new entrants and the number of high schools needs to be reconsidered. In other words, the aim is to reconsider (reducing in our case) the number of schools regarding the rate of student entrance and population size. Originality/value We propose a novel allocation-location problem, considering the efficiency concept based on data envelopment analysis. In most location models, a predetermined capacity is associated with each server. In this article, we propose a new joint model in the efficiencies of the servers are considered as their capacities.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.