Improving the accessibility to public schools in urban areas of developing countries through a location model and an analytical framework

The location of primary public schools in urban areas of developing countries is the focus of this study. In such areas, new schools and modification of the current schools are required, and this process should be developed using rational and broad supporting tools for decision makers, such as optimization models. We propose a realistic coverage location model and a framework to analyze the location of schools. Our approach considers the existing schools and their resizing, the best locations of the new schools that may have different capacities, population coverage, walking distances and budget provisions for building and updating schools. As a case study, we assess the current primary school network in Ciudad Benito Juarez to provide managerial insights. Through the proposed framework, we analyze the current locations of schools and decisions to be made by considering future scenarios in different time periods. The proposed model is quite flexible and easy to adapt to new considerations, allowing it to be applied to regions in developing countries under similar conditions.

Ambulance Locations in a Tiered Emergency Medical System in a City

This paper deals with optimizing the location of ambulance stations in a two-tiered emergency medical system in an urban environment. Several variants of station distribution are calculated by different mathematical programming models and are evaluated by a detailed computer simulation model. A new modification of the modular capacitated location model is proposed. Two ways of demand modelling are applied; namely, the aggregation of the ambient population and the aggregation of permanent residents at the street level. A case study of the city of Prešov, Slovakia is used to assess the models. The performance of the current and proposed sets of locations is evaluated using real historical data on ambulance trips. Computer simulation demonstrates that the modular capacitated location model, with the ambient population demand, significantly reduces the average response time to high-priority patients (by 79 s in the city and 62 s in the district) and increases the percentage of high-priority calls responded to within 8 min (by almost 4% in the city and 5% in the district). Our findings show that a significant improvement in the availability of the service can be achieved when ambulances are not accumulated at a few stations but rather spread over the city territory.

Modeling of Mono-Commodity Multi-Location Linear Programming Techniques for Determining Optimum Transportation Network of a Manufacturing Industry

This research on Modeling and Application of Mono-Commodity Multi-Location Linear Programming Techniques For Determining Optimum Transportation Network was carried out at a Manufacturing Industry in Lagos, which comprises of two plants, three depots and twenty retailers axis. The model was analyzed using Micro Soft Excel Software. The analysis to determine the optimal transportation network was carried out in two phases by considering numbers of truckload transported and each commodity from plants to depots and depots to retailers and their optimals. It was discovered that the existing practices transportation cost for truckloads moving from plant to retailers is N3,544,000,000,000 and when optimized, cost is N1,932,650,000,000 while considering each product the optimized transportation cost is N1,871,065,369,000. This implies that the transportation network generated considering each product will yield 47.2% gain in profit than existing network. Hence, it is recommended that mono-commodity multi-location transportation network be used. Keywords: [EXCEL Software, Mono-Commodity Multi-Location Model, Transportation Cost, Transportation Model, Transportation Network.].

A MILP facility location model with distance value adjustments for demand fulfillment using Google Maps

In this manuscript, a facility location model was designed to support logistics operations, considering service distance limitations for demand fulfillment and a list of candidate locations within a supply chain. Consequently, an allocation model was designed using Mixed-Integer Linear Programming (MILP), in which a finite number of demand nodes could be satisfied by a set of supply nodes, considering not only the costs related to these locations but also restrictions aimed at improving the level of service based on distance. Besides, an integrated solution scheme was proposed that includes a macro in VBA language that calculates the distance between nodes using the web mapping service developed by Google Maps and solving the model through a branch and cut algorithm. Subsequently, a case study was executed where the supply operation of an important Colombian retail company is analyzed. The results reflected positive effects not only on costs but also on the prioritization of average distance traveled and on the satisfaction of store demand by distribution centers. Thus, the conditions in which the implementation of this model provides strategic benefits were verified, functioning as a tool to support decision making.

Research on Multi-Period Hydrogen Refueling Station Location Model in Jiading District

The construction of hydrogen refueling stations is an important part of the promotion of fuel cell vehicles. In this paper, a multi-period hydrogen refueling station location model is presented that can be applied to the planning and construction of hydrogen infrastructures. Based on the hydrogen demand of fuel cell passenger cars and commercial vehicles, the model calculates the hydrogen demand of each zone by a weighting method according to population, economic level and education level. Then, the hydrogen demand of each period is calculated using the generalized Bass diffusion model. Finally, the set covering model is improved to determine the locations of the stations. The new model is applied to the scientific planning of hydrogen refueling stations in Jiading District, Shanghai; the construction location and sequence of hydrogen refueling stations in each period are given, and the growth trend of hydrogen demand and the promoting effect of hydrogen refueling stations are analyzed. The model adopted in this model is then compared with the other two kinds of node-based hydrogen refueling station location models that have previously been proposed.

Multiobjective Site Selection Model for Emergency Shelter Facilities in Urban Areas

Industrial and economic development is primarily applied to densely populated urban areas. If a sudden disaster occurs in such areas, the consequences can be severe. Shelter facility location affects the implementation of postdisaster relief work. This study explored residents’ perceived utility of evacuation time, their risk utility for road blocking, and the cost factors associated with constructing shelter facilities in the context of governance. A location model for emergency shelter facilities in cities was established on the basis of the aforementioned factors. Because the resolution of the random-weighted genetic algorithm (RWGA) is susceptible to influence from random weights, a robustness random-weighted method (RRWM) was developed. The validity and feasibility of the location model were examined through numerical analysis. Finally, the convergence of the RRWM was analyzed and compared with that of the RWGA and a single-objective genetic algorithm. The results revealed that the proposed algorithm exhibited satisfactory performance and can assist in evaluation and decision-making related to the selection of urban shelter facility locations.