Browsing by Author "SHOBAYO, SULAIMON"

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    A HYBRID LINEAR PROGRAMMING MODEL AND GENETIC ALGORITHM APPROACH FOR RESOURCES ALLOCATION IN DISASTER RESPONSE
    (2023) SHOBAYO, SULAIMON
    Efficient allocation of resources such as emergency personnel and equipment plays a major role in disaster scenarios by minimizing the response time. Limited resources concerns using resources as productively as possible. This research focuses on novel development of a hybrid linear programming model and genetic algorithm approach for resource allocation in accident disaster response. The objective is to optimize the total response-time for allocation of resources to affected areas and populations and enhance the efficiency and effectiveness of disaster response operations. This model combines the strengths of integer linear programming, which provides a systematic framework for the minimization of the total response time, and the Genetic Algorithms, which handle the case of complex and dynamic problem spaces. The GA leverages on the model formulated in the ILP trade-off to handle the complex based spaces which are utilized to search for near-optimal solutions within the problem space. The model considers various factors such as distance between resources and number of affected areas, capacity of affected area, and resource capacities. The objective function minimizes the response time by optimizing the distance between the resources and number of affected areas, while the constraints are, resources allocation, and capacity area. The result shows an improved and efficient outcome to response operations in minimizing response time to reaching affected area and maximizing coverage area with available resources. The outcomes enables decision-makers to make informed and optimized choices during critical situations by improving overall response outcome.