Implementation of a fixing strategy and parallelization in a recent global optimization method

Electromagnetism-like Mechanism (EM) heuristic is a population-based stochastic global optimization method inspired by the attraction-repulsion mechanism of the electromagnetism theory. EM was originally proposed for solving continuous global optimization problems with bound constraints and it has been shown that the algorithm performs quite well compared to some other global optimization methods. In this work, we propose two extensions to improve the performance of the original algorithm: First, we introduce a fixing strategy that provides a mechanism for not being trapped in local minima, and thus, improves the effectiveness of the search. Second, we use the proposed fixing strategy to parallelize the algorithm and utilize a cooperative parallel search on the solution space. We then evaluate the performance of our study under three criteria: the quality of the solutions, the number of function evaluations and the number of local minima obtained. Test problems are generated by an algorithm suggested in the literature that builds test problems with varying degrees of difficulty. Finally, we benchmark our results with that of the Knitro solver with the multistart option set

A symmetric rank-one Quasi-Newton line-search method using negative curvature directions

We propose a quasi-Newton line-search method that uses negative curvature directions for solving unconstrained optimization problems. In this method, the symmetric rank-one (SR1) rule is used to update the Hessian approximation. The SR1 update rule is known to have a good numerical performance; however, it does not guarantee positive definiteness of the updated matrix. We first discuss the details of the proposed algorithm and then concentrate on its numerical efficiency. Our extensive computational study shows the potential of the proposed method from different angles, such as; its second order convergence behavior, its exceeding performance when compared to two other existing packages, and its computation profile illustrating the possible bottlenecks in the execution time. We then conclude the paper with the convergence analysis of the proposed method

Parallel algorithms for nonlinear optimization

Parallel algorithm design is a very active research topic in optimization as parallel computer architectures have recently become easily accessible. This thesis is about an approach for designing parallel nonlinear programming algorithms. The main idea is to benefit from parallelization in designing new algorithms rather than considering direct parallelizations of the existing methods. We give a general framework following our approach, and then, give distinct algorithms that fit into this framework. The example algorithms we have designed either use procedures of existing methods within a multistart scheme, or they are completely new inherently parallel algorithms. In doing so, we try to show how it is possible to achieve parallelism in algorithm structure (at different levels) so that the resulting algorithms have a good solution performance in terms of robustness, quality of steps, and scalability. We complement our discussion with convergence proofs of the proposed algorithms

Distributed Decision Making: A Multiagent Decision Support System For Street Management

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2005Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2005Bu çalışmada, işbirlikçi dağıtık bir insan organizasyonundaki karar etkinliğinin, taktik ve stratejik seviyelerde dağıtık karar destek araçlarıyla arttırılabileceği öngörülmüştür. Çok ajanlı mimariye dayalı ve kullanıcıların karar süreçlerinde aktif olarak yer aldığı yeni bir dağıtık karar destek sistemi önerilmiştir. Sistemin performans modeli bulanık bilişsel haritalama yönetimi kullanılarak oluşturulmuştur. Önerilen sistemin uygulanabilirliği, Java ortamında geliştirilen bir örnek program ile test edilmiştir ve uygulama alanı olarak dağıtık karar vermenin iyi bir örneği olan cadde yönetim sistemi seçilmiştir. Örnek uygulama başarıyla gerçekleştirilmiştir.In this study, it is suggested that, decisional effectiveness in a cooperative distributed human system can be increased by distributed decision support tools at tactical and strategic levels. A new distributed decision support system based on multiagent architecture is proposed, in which human agents are also actively involved in the decision process. The performance model of the system was established using fuzzy cognitive map approach. The applicability of the proposed system was tested on a sample implementation program developed in Java environment and street management is selected as the application domain since it is a good example of distributed decision making. The sample implementation was successfully realized.Yüksek LisansM.Sc

Multiagent cooperation for solving global optimization problems: an extendible framework with example cooperation strategies

This paper proposes the use of multiagent cooperation for solving global optimization problems through the introduction of a new multiagent environment, MANGO. The strength of the environment lays in itsflexible structure based on communicating software agents that attempt to solve a problem cooperatively. This structure allows the execution of a wide range of global optimization algorithms described as a set of interacting operations. At one extreme, MANGO welcomes an individual non-cooperating agent, which is basically the traditional way of solving a global optimization problem. At the other extreme, autonomous agents existing in the environment cooperate as they see fit during run time. We explain the development and communication tools provided in the environment as well as examples of agent realizations and cooperation scenarios. We also show how the multiagent structure is more effective than having a single nonlinear optimization algorithm with randomly selected initial points

In a real-life setting, direct-acting antivirals to people who inject drugs with chronic hepatitis c in Turkey

Background: People who inject drugs (PWID) should be treated in order to eliminate hepatitis C virus in the world. The aim of this study was to compare direct-acting antivirals treatment of hepatitis C virus for PWID and non-PWID in a real-life setting. Methods: We performed a prospective, non-randomized, observational multicenter cohort study in 37 centers. All patients treated with direct-acting antivirals between April 1, 2017, and February 28, 2019, were included. In total, 2713 patients were included in the study among which 250 were PWID and 2463 were non-PWID. Besides patient characteristics, treatment response, follow-up, and side effects of treatment were also analyzed. Results: Genotype 1a and 3 were more prevalent in PWID-infected patients (20.4% vs 9.9% and 46.8% vs 5.3%). The number of naïve patients was higher in PWID (90.7% vs 60.0%), while the number of patients with cirrhosis was higher in non-PWID (14.1% vs 3.7%). The loss of follow-up was higher in PWID (29.6% vs 13.6%). There was no difference in the sustained virologic response at 12 weeks after treatment (98.3% vs 98.4%), but the end of treatment response was lower in PWID (96.2% vs 99.0%). In addition, the rate of treatment completion was lower in PWID (74% vs 94.4%). Conclusion: Direct-acting antivirals were safe and effective in PWID. Primary measures should be taken to prevent the loss of follow-up and poor adherence in PWID patients in order to achieve World Health Organization’s objective of eliminating viral hepatitis