Matrix-based modeling for multi-objective resource management optimization in construction infrastructure and transport operations
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Date
2023-12-19
Authors
Φαρμάκης, Παναγιώτης
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Abstract
Optimization refers to evaluating available alternatives to choose the most efficient. It is a process with numerous applications in all aspects of life, from simple daily activities (selecting a route and spending money) to decision support at the strategic level. In engineering design, optimization is the systematic procedure of defining the optimal solution according to a set of prioritized constraints and criteria for increasing effectiveness (usually minimizing costs or maximizing productivity) by improving processes through better resource engagement and usually follows the Analysis where mathematical models and scientific principles are employed for predicting design results. In small-case problems, the size, in combination with knowledge and previous experience, simplifies things to a great extent. However, as the magnitude and complexity increase, developing intelligent computational tools is the only pathway to achieve management objectives.
This Doctoral Thesis aims to develop a holistic methodology for efficiently considering multi-objective optimization problems in Transportation Infrastructure and Construction Management of Civil Engineering science. More specifically, decision parameters such as priority in service, οne-to-one matching or assignment between several alternatives with or without alternative options are appropriately formulated. Furthermore, matrix algebra is employed to calculate the fitness function to evaluate how close a candidate solution is to achieving the set aims. Moreover, this Thesis also illustrates a spatial approach based on Ray Casting Algorithm implementation for efficiently exploiting any given space for problems where the optimal placement of facilities or infrastructure is the issue.
These methodologies developed in the framework of this doctoral Thesis, with slight variations adapted to each problem's particularities, are applied in three of the most critical issues in the relative fields, which are the Construction Site Layout Planning (CSLP) for both spacious and congested sites, the Hub-and-Spoke (H&S) network modeling focused on Short Sea Shipping (SSS) transportation, and the supply chain & logistics management at operational level dealing with cross-docking operation in the distribution centers scheduling including vehicle route planning concerns (CDVRP). The expected output and the contribution of this study are to validate the models' robustness in providing acceptable (near-optimal) solutions in terms of solution quality (reflecting optimization objectives and constraint/preference satisfaction) and computational efficiency (acceptable running time) for all case studies and operational scenarios providing a useful tool for well-informed decision supporting.
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Keywords
Resource management, Construction Site Layout Planning (SCLP), Hub and Spoke network system (H&S), Cross docking systems in supply chain (CD), Optimization, Genetic algorithms