Browsing by Subject "Bi-objective Optimization"

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Open Access
Covering vehicle routing problem: applications for refugee related services
(2018-07) Buluç, Elfe Naz
The world is facing a refugee crisis because of the ongoing war in Syria, and it is important to develop refugees' life conditions and increase their integration to the host communities. There are several services given to refugees to improve humanitarian development. The distribution of cash and e-vouchers to refugees and the routing of trucks which provide Child Friendly Spaces to vulnerable refugee children are addressed in this study. Both problems have similar characteristics as they provide services using mobile vehicles. The distribution of e-vouchers problem is applied for two scenarios, where local distribution centers are opened to cover an area, and a combination of local distribution centers and hand-tohand delivery is conducted to increase the accessibility. The given problems are categorized as Covering Vehicle Routing Problem and Covering Vehicle Routing Problem with Integrated Tours which are introduced to the literature. The performance of the proposed models is tested and a sensitivity analysis on the problem parameters is given. Three optimization based heuristics are proposed to improve solving times. The proposed solutions are applied to a real life case of city Kilis. In order to apply the models to the routing of Mobile Child Friendly Spaces problem, a bi-objective version of the proposed models is given where the aim is to minimize the unsatis ed demand while minimizing travelled distance. -constraint method is applied to solve the bi-objective application and all Pareto Optimal solutions are obtained.
Open Access
A mathematical modeling approach for managing regional blood bank operations
(2018-09) Dilaver, Halit Metehan
Blood bank operations are complex affairs since they involve supply chain management of highly perishable goods such as whole blood and blood products. The Turkish Red Crescent (TRC), who is the main responsible organization in Turkey for collection, testing, separation and distribution of whole blood and blood products, is in constant need of optimizing its operational decisions. We propose a mathematical modeling approach for managing the blood bank operations in the TRC that include the decisions of donation collection, production and distribution to demand points (hospitals). The model minimizes system cost while ensuring maximum level of demand satisfaction. For this purpose, a lexicographic approach is used that first determines the maximum amount of demand that can be satisfied and then solves a cost minimization model, which is a linear mixed-integer programming model. Observing that it may not be possible to find the optimal solution of this model in reasonable time for some real-life problem sizes, we develop a customized heuristic approach for the problem. We demonstrate that the heuristic algorithm provides good quality solutions in negligible time through computational experiments. We finally examine a bi-objective extension of the cost minimization problem, where the quality of the separated blood product is considered alongside system cost. We solve the resulting bi-objective programming problems using the Ɛ- Constraint Method. This extension allows the decision maker to observe the trade-off between cost and quality and implement her most preferred solution among the non-dominated solutions.
Open Access
A prize collecting Steiner Tree approach to least cost evaluation of grid and off-grid electrification systems
(2017-07) Bölükbaşı, Gizem
The lack of access to electricity in developing countries necessitates spatial electricity planning for guiding sustainable electri cation projects that evaluate the costs of centralized systems vis-a-vis decentralized approaches. Heuristic approaches have been widely used in such electri cation problems to nd feasible, cost e ective solutions; however, most of the time global optimality of these solutions is not guaranteed. Our thesis through its modeling approach provides a new methodology to nd the least cost solution to this electri cation problem. We model the spatial network planning problem as Prize Collecting Steiner Tree problem which would be base for a decision support tool for rural electri cation. This new method is systematically assessed using both randomly generated data and real data from rural regions across Sub- Saharan Africa. Comparative results for the proposed approach and a widely used heuristic method are presented based on computational experiments. Additionally, a bi-objective approach that permits to take carbon emission level into the account is implemented and experimented with numerical data.