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Turkey's Aegean region is a very suitable region for fruit production in terms of climatic conditions and soil characteristics. Fruit and vegetable production in the Aegean region has an important position in terms of Turkey's agricultural economy. The fruit growing sector has a very important place in Turkey's agricultural economy. The aim of the study is to prevent unbalanced fruit production in the Aegean region and to ensure more efficient fruit growing. In the study, it was aimed to assign a balanced production of fruits grown under different conditions in provinces with different characteristics in the Aegean region. For the assignment problem, the conditions of the cities in the Aegean region and the growing conditions of the fruits are considered together. These conditions are altitude, temperature, soil quality, climate, humidity, labor and irrigation. Conditions for fruit production were analyzed with the AHP method and factor weights were calculated. ARAS and Fuzzy Logic methods were used to solve the assignment problem of fruits. These methods enable to reach the result by digitizing the non-computable features of a particular situation. Aydın, Manisa, Denizli and Afyonkarahisar provinces have been proposed, respectively, for the production of figs, grapes, thyme and cherries, which have high industrial value and export income. The study has shown that unbalanced production can be prevented by assigning fruits and vegetables in this way in every region of the country. As a result, the country's agricultural lands will be used effectively and the contribution of agriculture to the national economy will increase. [ABSTRACT FROM AUTHOR]

The multi-resource generalized assignment problem (MRGAP) is the assignment of jobs to agents under capacity constraints to minimize the total assignment. In this problem, each agent has multiple resources, each job is assigned to only one agent, and multiple jobs can be assigned to one agent. In the MRGAP problem, it is essential to distribute the loads in balance to the agents. In the literature, for balancing agent loads, bottleneck MRGAP with the aim of minimizing the maximum agent load, and balanced assignment MRGAP models with the aim of minimizing the difference between the maximum agent load and the minimum agent load have been proposed. In this study, the sum of load squares model has been adapted for MRGAP, as well as a new goal programming MRGAP model and a matheuristic algorithm for the solution of this model are developed. The performances of the proposed model and the algorithm were compared with the models taken from the literature by using randomly derived test problems. The quality of the obtained solutions is determined by considering the maximum load, coefficient of variation and total load criteria. The test results are evaluated in terms of these three criteria. The results obtained revealed the success of the proposed goal programming model and the matheuristic algorithm. [ABSTRACT FROM AUTHOR]

In this study, the optimization of the rotation of doctors in some certain branches who work in the Ministry of Health to some institutions was done regarding the doctor’s work experience points, seniority, personal preferences; the present number of the stuff in the health institutions of the ministry and their future needs. Considering their preference priority, we attempted to appoint doctors to one of the institutions, according to their work experience point, seniority, the length of service and the preferences of the institution they are currently working and those of the one they want to be assign. In this assignment, the points such as the number of the staff to be employed in the institution; the number of the staff working in the institution currently; the number of the staff demanded; the number of the staff to leave the institution by assigned; and the possibility that some of the staff may be assign to other institutions should be considered to meet the needs of the institutions and to assign doctors to different institutions in a balanced way. The genetic algorithm was used as the method of the solution of the problem. In genetic algorithm after the mutation operation and the transposition on the chromosomes, it was observed that some of the candidates might be appointed to the institutions they have not preferred. This problem was solved by assigning the candidate to one of the institutions (to their prior preferences) with the help of the chromosome correction algorithm. In the problem, the method we developed was tested by constructing different data sets with the help of a data set constructing function which simulates actual data. To solve the problem, C#.NET Express programming language and MS SQL 2005 Express data sets were used. [ABSTRACT FROM AUTHOR]

In this study, we consider location selection problem for central cash offices and cash management decisions for ATM's for İş Bank. Cash Management System involves the cash amounts held in ATM's, branches, central cash offices and cash transfers between central cash offices and ATMs or branches. Cash amount held in ATM's and branches affects the customer satisfaction and also, together with cash transfers, it costs considerable amount to the bank. Cash management system involves two sub problems. Those are selection of location for central cash offices, assignment of ATM's and branches to central cash offices, and determining cash management policies for ATM's. Those problems are discussed in steps, solution approaches are applied for Black Sea Region and results are discussed. The aim of this project is, under resource constraints, the optimization of the cash management system considering the related costs and customer satisfaction. [ABSTRACT FROM AUTHOR]

The Hungarian algorithm is one of the most well-known methods in computer science literature. By this method, in each step the cost matrix is systematically reduced to a new matrix in order to obtain an optimal solution for the assignment problem. The subroutine of the algorithm includes determining the minimum number of lines needed to cover all zeros in the reduced cost matrix and modifying the matrix according to the number of lines. In this paper, firstly the methods in literature including the covering all zeros with a minimum number of lines are examined, then a new method is proposed and computational experiments are discussed. [ABSTRACT FROM AUTHOR]

The Hungarian algorithm is one of the most well-known methods in computer science literature. By this method, in each step the cost matrix is systematically reduced to a new matrix in order to obtain an optimal solution for the assignment problem. The subroutine of the algorithm includes determining the minimum number of lines needed to cover all zeros in the reduced cost matrix and modifying the matrix according to the number of lines. In this paper, firstly the methods in literature including the covering all zeros with a minimum number of lines are examined, then a new method is proposed and computational experiments are discussed. [ABSTRACT FROM AUTHOR]