Ortalama-varyans portföy optimizasyonunda genetik algoritma uygulamaları üzerine bir literatür araştırması

Mean-variance portfolio optimization model, introduced by Markowitz, provides a fundamental answer to the problem of portfolio management. This model seeks an efficient frontier with the best trade-offs between two conflicting objectives of maximizing return and minimizing risk. The problem of determining an efficient frontier is known to be NP-hard. Due to the complexity of the problem, genetic algorithms have been widely employed by a growing number of researchers to solve this problem. In this study, a literature review of genetic algorithms implementations on mean-variance portfolio optimization is examined from the recent published literature. Main specifications of the problems studied and the specifications of suggested genetic algorithms have been summarized

Determining the optimum production portfolio in agricultural sector : province of Denizli case

Agriculture is a field which is critically important for the economy of every country. Countries pursue different agricultural production strategies in different regions in accordance with their needs. In this study, a production planning model was developed based on Modern Portfolio Theory for the production of summer and winter vegetables in Denizli, which has a significant agricultural production potential for the Aegean region. The historical data of the specified products were obtained from Turkish Statistical Institute (TUIK). As the analysis method, Markowitz mean variance model and efficient frontier concepts were used. The optimum production portfolios, which have different product ranges and through which the manufacturers can make maximum profit according to their risk appetite, were determined. This study serves as a guide way to the manufacturers for the cultivation plans in future seasons.peer-reviewe

Determining the optimum production portfolio in agricultural sector : province of Denizli case

Agriculture is a field which is critically important for the economy of every country. Countries pursue different agricultural production strategies in different regions in accordance with their needs. In this study, a production planning model was developed based on Modern Portfolio Theory for the production of summer and winter vegetables in Denizli, which has a significant agricultural production potential for the Aegean region. The historical data of the specified products were obtained from Turkish Statistical Institute (TUIK). As the analysis method, Markowitz mean variance model and efficient frontier concepts were used. The optimum production portfolios, which have different product ranges and through which the manufacturers can make maximum profit according to their risk appetite, were determined. This study serves as a guide way to the manufacturers for the cultivation plans in future seasons.peer-reviewe

ÜLKE KAYNAKLARININ VERİMLİ KULLANIMI: 4x4 ARAMA VE KURTARMA ARACI SEÇİMİNDE AHS VE TOPSIS YÖNTEMLERİNİN UYGULAMASI

ÖZET Sosyal devlet anlayışının gelişmesine bağlı olarak kamu giderleri artmış ve elde bulunan sınırlı kaynakların hizmet kalitesinden ödün verilmeden verimli kullanımı zorunlu hale gelmiştir. Devletin üstlendiği görevler nedeniyle kamu kurumlarının belirli harcamalar yapmaları gerekmektedir. Bu harcamaların en önemli kalemlerinden birisi de araç alımlarıdır. Bu çalışmada, 4x4 arama kurtarma aracı seçiminde Analitik Hiyerarşi Süreci (AHS) ve TOPSIS yöntemlerinin kullanımı ele alınmıştır. Anahtar Kelimeler: Araç seçimi, AHS, TOPSIS EFFICIENT USE OF COUNTRY RESOURCES: PRACTICE OF THE AHP AND TOPSIS METHODS IN SELECTION OF 4x4 SEARCH AND RESCUE (SAR) VEHICLE ABSTRACT Depending on the development of the sense of social state, public expenditures increased and the efficient use of limited resources without compromising the service quality has become a necessity. Due to the tasks undertaken by the state, public institutions need to make certain expenditures. One of the most important item in expenditures is the vehicle purchases. In this study, the selection of 4x4 SAR vehicle using Analytical Hierarchy Process (AHP) and TOPSIS methods is discussed. Key words: Vehicle selection, AHP, TOPSI

Heuristic methods for optimal portfolio management

Günümüzde ticaretin küreselleşmesi ile birlikte dünyada finans piyasaları da hızla gelişmiştir. Bu ilerlemelerin sonucunda finans alanının bir alt dalı olan portföy yönetimi de oldukça önem kazanmıştır. Geçmişte, yatırımcılar portföylerini geleneksel portföy teorisi yaklaşımına göre oluşturmaktadırlar. İkinci yöntem ise, modern portföy teorisi yaklaşımına göre portföy oluşturmaktır. Modern portföy teorisi yaklaşımında kullanılan temel model H. Markowitz’in geliştirdiği ortalama varyans modelidir. Küreselleşme ile birlikte dünyada yatırım olanakları genişlemiş ve portföye dahil edilebilecek menkul kıymet sayısı artmıştır. Yatırımcı açısından fazla sayıda menkul kıymetten oluşan bir portföyün işlem maliyeti artacak ve kontrolü zorlaşacaktır. Bu durumda, yatırımcı aynı risk ve getiri düzeyinde sınırlı sayıda menkul kıymete yatırım yapmak istemektedir. Bu kısıtın eklenmesi sonucunda portföy optimizasyonu problemi literatürde yer alan NP-Zor sınıfında bir probleme dönüşmüştür. Bu tür problemlerin, belirli bir zaman diliminde çözümü zor olduğundan sezgisel yöntemler geliştirilmiştir. Tezde, portföy optimizasyonu problemi çözümü için genetik algoritma, parçacık sürü optimizasyonu ve yapay arı kolonisi algoritmaları geliştirilmiştir. Geliştirilen sezgisel metotlar önde gelen dünya borsa endekslerine ve Borsa İstanbul endeksine uygulanmıştır. Önerilen algoritmalar ile bulunan sonuçlar etkin sınıra yakınsamaktadır ve yatırımcıya portföy oluşturma sürecinde yardımcı olacaktır.Today, financial markets have rapidly developed with the globalization of trade. As a result of this progress, portfolio management as a sub-branch of finance has also significantly gained importance. In the past, investors used to decide their portfolio according to the traditional portfolio theory. Today on the other hand, portfolio is created according to the modern portfolio theory proposed by H. Markowitz due to the increase in the number of assets to be held in a portfolio. It is desired to invest in a limited number of assets with the same level of risk and return. Therefore, the portfolio optimization problem with cardinality constraints turns out to be in NP-hard class of problems. Metaheuristic approaches are usually applied to solve this problem since it is often not possible to reach optimal solutions within acceptable time. In this thesis, a genetic algorithm, a particle swarm optimization algorithm and an artificial bee colony algorithm are developed to solve this problem studied. These proposed solution approaches are applied to primary world market data sets and Istanbul market data sets. Computational results confirm that proposed solution approaches are useful tools to converge an efficient frontier that may help the investors to select portfolio

Kademeli mesai saati ile trafik sıkışıklığının azaltılması

Today traffic congestion is one of the most important problems that adversely affect human life in many aspects. Traffic congestion is experienced during the morning and evening peak hours which have the highest traffic intensity. The main reason of the traffic congestion during the peak hours is that the work start and finish times of the firms in both private and public sectors are very close. Spreading the travel demand during peak hours for longer time period is a means to reduce the traffic congestion during the peak hours. The staggered working hours is one of the methods used for this purpose. In this study, a mathematical model is proposed to reduce the traffic congestion by using the staggered working hours strategy. The aim of the model is to find the working hours of the each destination node by considering the travel demands between origin-destination nodes, the paths and the capacities of the roads. A 0-1 integer goal programming model is developed for this purpose. The developed model is solved for different sized data sets. The results show that the staggered working hours strategy will significantly reduce the peak hours traffic congestion

Examination timetabling problem with scarce resources: A case study

Examination timetabling problem (ETP) is one of the hardest administrative tasks that has to be undertaken at each semester in all faculties. Although the major structure of the problem remains intact, requirements may change from faculty to faculty causing major changes in the solution procedures. The number of academic staff and the level of infrastructures of newly established universities cannot keep up with the increasing number of departments and students. This scarcity brings several additional constraints to the ETP. In this study, we propose a two stage solution procedure for the ETP of such universities. We apply our solution method to a real problem. We show that better feasible solutions can be found in shorter computation times compared to commercial softwares. Moreover we show that the total examination period length can be reduced from seven days to six days with the proposed method. [Received 17 June 2017; Revised 23 April 2018; Accepted 7 July 2018]. Copyright © 2018 Inderscience Enterprises Ltd

Ortalama-varyans portföy optimizasyonunda genetik algoritma uygulamaları üzerine bir literatür araştırması

Markowitz’in ortaya koymuş olduğu ortalama-varyans portföy optimizasyonu, portföy yönetimi problemine temel bir cevap vermiştir. Bu model, getirinin en büyüklenmesi ve riskin en küçüklenmesi gibi iki çakışan amaç arasındaki en iyi ödünleşimi ile bir etkin sınır aramaktadır. Bir etkin sınır belirleme probleminin NP-Zor olduğu bilinmektedir. Problemin karmaşıklığı nedeniyle, giderek artan sayıda araştırmacı bu problemi çözmek için genetik algoritmaları kullanmışlardır. Bu çalışmada, mevcut literatürdeki genetik algoritmaların ortalama-varyans portföy optimizasyonu uygulamaları incelenmiştir. Çalışılmış olan problemlerin ana özellikleri ve önerilen genetik algoritma karakteristikleri özetlenmiştir