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- An Application of Preference-Inspired Co-Evolutionary Algorithm to SectorizationPublication . Ozturk, E. Goksu; Rocha, Pedro; Sousa, Filipe; Lima, Maria Margarida; Rodrigues, Ana Maria; Soeiro Ferreira, José; Catarina Nunes, Ana; Lopes, Isabel Cristina; Oliveira, CristinaSectorization problems have significant challenges arising from the many objectives that must be optimised simultaneously. Several methods exist to deal with these many-objective optimisation problems, but each has its limitations. This paper analyses an application of Preference Inspired Co-Evolutionary Algorithms, with goal vectors (PICEA-g) to sectorization problems. The method is tested on instances of different size difficulty levels and various configurations for mutation rate and population number. The main purpose is to find the best configuration for PICEA-g to solve sectorization problems. Performancemetrics are used to evaluate these configurations regarding the solutions’ spread, convergence, and diversity in the solution space. Several test trials showed that big and medium-sized instances perform better with low mutation rates and large population sizes. The opposite is valid for the small size instances.
- A resectorization of fire brigades in the north of PortugalPublication . Lima, Maria Margarida; Ozturk, E. Goksu; Sousa, FIlipe; Lopes, Isabel Cristina; Teles Oliveira, Cristina; Rodrigues, Ana Maria; Catarina Nunes, Ana; Soeiro Ferreira, JoséSectorization can be regarded as a division of a territory into smaller regions to deal with a complex problem involving multiple-criteria. Resectorization intends to achieve another sectorization, according to some new conditions but avoiding substantial changes. An example of this can be the distribution of geographical areas by fire brigades. In Portugal, fire brigades must protect and rescue the population in the areas surrounding their fire stations. So we will use the current sectorization, the geographic and population characteristics of the areas and the fire brigades’ response capacity to provide an optimised resectorization, in order to decrease rescue time. To achieve that, we will use a decision support system using different optimisation methods, such as Non-dominated Sorting Genetic Algorithm (NSGA II), which provides an effective sectorization concerning compactness and equilibrium criteria.