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- Sectorization of a Parcel Delivery ServicePublication . Mostardinha, Mafalda; Escobar Hernández, Pablo; Lopes, Isabel Cristina; Rodrigues, Ana MariaThis paper explores the problem of sectorization of a parcel delivery service that wants to assign an action region to each of its teams, regarding the number of deliveries scheduled for each zone, so that there is a balanced service amongst sectors, covering contiguous zones, and considering limited capacities for the teams. Besides being relatively easy to model, the available optimization tools and software provide poor results when dimension increases in these types of problems, with computational capacity exceeding. In this paper an integer programming model, combined with an heuristic to return a faster solution, was implemented to solve a sectorization problem in two different situations. The main advantage of the strategy proposed, compared to previous ones, is its simplicity and easy implementation while still returning an optimal solution.
- 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.
- Sectorization for managing maintenance techniciansPublication . Lopes, Isabel Cristina; Rodrigues, Ana Maria; Oliveira, Cristina; Soeiro Ferreira, José; Cortinhal, Maria Joãobetter organization of the region, or to simplify a large problem into smaller sub-problems, or to obtain groups with similar characteristics. To evaluate the quality of the solutions, three criteria are commonly used: Equilibrium (the sectors should be identical portions of the whole), Compactness (regular forms like circles are preferred, avoiding sectors shaped with ‘tentacles’), and Contiguity (avoid sectors divided into portions). Depending on the application, other criteria can also be considered, therefore multicriteria approaches should be used. Sectorization problems can arise when designing political districts, defining sales territories, managing routes for distribution of goods or collecting municipal waste, assigning neighborhoods to schools, locating health care services, police stations, or fire brigades. This talk will address the sectorization in an elevator maintenance company, where the definition of the zones assigned to each technician have an impact on the company’s efficiency and quality of service. In order to define the best sectorization, not only the maintenance plan should be considered, but also the unplanned interventions. We will discuss the different solution methods that can be applied to this case.
- Creating homogeneous sectors: criteria and applications of sectorizationPublication . Lopes, Isabel Cristina; Lima, Maria Margarida; Ozturk, E. Goksu; Rodrigues, Ana Maria; Nunes, Ana Catarina; Oliveira, Cristina; Soeiro Ferreira, José; Rocha, PedroSectorization is the process of grouping a set of previously defined basic units (points or small areas) into a fixed number of sectors. Sectorization is also known in the literature as districting or territory design, and is usually performed to optimize one or more criteria regarding the geographic characteristics of the territory and the planning purposes of sectors. The most common criteria are equilibrium, compactness and contiguity, which can be measured in many ways. Sectorization is similar to clustering but with a different motivation. Both aggregate smaller units into groups. But, while clustering strives for inner similarity of data, sectorization aims at outer homogeneity [1]. In clustering, groups should be very different from each other, and similar points are classified in the same cluster. In sectorization, groups should be very similar to each other, and therefore very different points can be grouped in the same sector. We classify sectorization problems into four types: basic sectorization, sectorization with service centers, resectorization, and dynamic sectorization. A Decision Support System for Sectorization, D3S, is being developed to deal with these four types of problems. Multi-objective genetic algorithms were implemented in D3S using Python, and a user-friendly web interface was developed using Django. Several applications can be solved with D3S, such as political districting, sales territory design, delivery service zones, and assignment of fire stations and health services to the population.