The optimal location of airport fire stations: a fuzzy multi‐objective programming and revised genetic algorithm approach

A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms

“…It is appreciated that the optimum solution is the one which minimizes the sum of losses from fire and the cost of providing the service (Hogg, 1968). In detail, appropriate fire station locations can bring the following benefits (Tzeng and Chen, 1999): (a) it can shorten the distance between fire stations and accident sites so as to improve reaction time efficiency; (b) fire stations can be loaded to minimize overlap of fire station services, so as to utilize efficiently fire station resources; and (c) it can help determine the reasonable number of fire stations at a given area by considering an economical trade-off between the accident-loss cost and the total setup and operating costs of fire stations.…”

Optimizing Fire Station Locations for the Istanbul Metropolitan Municipality

“…Such location problems are discrete optimization problems and have attracted the interest of many researchers¸ including Valinski (1955), Toregas and ReVelle (1973), Doeksen and Oehrtman (1976), Plane and Hendrick (1977), Schilling (1982), Badri et al (1998), and Tzeng and Chen (1999). The problem is difficult to solve (Garey and Johnson 1979) and real-life applications with a large number of locations may require unacceptably long computation times and amounts of resources using standard exact solution approaches.…”

“…The problem is difficult to solve (Garey and Johnson 1979) and real-life applications with a large number of locations may require unacceptably long computation times and amounts of resources using standard exact solution approaches. Hence, many researchers, including Tzeng and Chen (1999), Cheung et al (2001), and Salhi and Gamal (2003), propose metaheuristics (e.g., genetic algorithms) for solving large-scale problems. Previous researchers, including Cheung et al (2001), Diwekar (2003), Badri et al (1998), and Araz et al (2007), also suggest multiobjective fire station location problems for incorporating strategic and operational objectives, such as considering politically favored sites or water availability of the site.…”

A decision support system for firebase location in a nature conservation area

“…Yet another such instance is the fuzzy multi-objective programming approach of Tzeng and Chen [60] in which a genetic algorithm was employed to come up with trade-off decisions in terms of the number of fire stations required at an international airport and where these fire stations should be located. A final example is the integer goal programming approach adopted by Badri et al [5] to solve their multi-objective model for urban fire station locations in which they considered seven objectives that are conflicting to some degree (including the minimisation of fixed costs, fire engine travel costs and fire engine travel times, as well as the maximisation of coverage capability).…”