Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

Optimization methods for the operating room management under uncertainty: stochastic programming vs. decomposition approach

The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.

Self-adapting parallel metric-space search engine for variable query loads

This research focuses on automatically adapting a search engine size in response to fluctuations in query workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computer resources to or from the engine. Our solution is to contribute an adaptive search engine that will repeatedly re-evaluate its load and, when appropriate, switch over to a dierent number of active processors. We focus on three aspects and break them out into three sub-problems as follows: Continually determining the Number of Processors (CNP), New Grouping Problem (NGP) and Regrouping Order Problem (ROP). CNP means that (in the light of the changes in the query workload in the search engine) there is a problem of determining the ideal number of processors p active at any given time to use in the search engine and we call this problem CNP. NGP happens when changes in the number of processors are determined and it must also be determined which groups of search data will be distributed across the processors. ROP is how to redistribute this data onto processors while keeping the engine responsive and while also minimising the switchover time and the incurred network load. We propose solutions for these sub-problems. For NGP we propose an algorithm for incrementally adjusting the index to t the varying number of virtual machines. For ROP we present an ecient method for redistributing data among processors while keeping the search engine responsive. Regarding the solution for CNP, we propose an algorithm determining the new size of the search engine by re-evaluating its load. We tested the solution performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud. Our experiments show that when we compare our NGP solution with computing the index from scratch, the incremental algorithm speeds up the index computation 2{10 times while maintaining a similar search performance. The chosen redistribution method is 25% to 50% faster than other methods and reduces the network load around by 30%. For CNP we present a deterministic algorithm that shows a good ability to determine a new size of search engine. When combined, these algorithms give an adapting algorithm that is able to adjust the search engine size with a variable workload.

Technical and economic resources management in smart grids using heuristic optimization methods

Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

The unfathomable secret remains: a reverse engineering study of SEO factors on Google's search engine

The vast majority of users don’t seek results beyond the second page offered by the search engine, so if a site fails to be among the top 20 (second page), it says that this page does not have good SEO and, therefore, is not visible to the user. The overall objective of this project is to conduct a study to discover the factors that determine (or not) the positioning of websites in a search engine.

Influence of Link Structure on Search Engine Result Pages of Online Nursery Shops

The primary objective of this thesis is to assess how the backlink portfolio structure and off site Search Engine Optimisation (SEO) elements influence ranking of UK based online nursery shops. The growth of the internet use demanded significant effort from companies to optimize and increase their online presence in order to cope with the increasing online competition. The new e-Commerce technology - called Search Engine Optimisation - has been developed that helped increase website visibility of companies. The SEO process involves on site elements (i.e. changing the parameters of the company's website such as keywords, title tags and meta descriptions) and off site elements (link building and social media marketing activity). Link Building is based on several steps of marketing planning including keyword research and competitor analysis. The underlying goal of keyword research is to understand the targeted market through identifying relevant keyword queries that are used by targeted costumer group. In the analysis, three types (geographic, field and company’s strategy related) and seven sources of keywords has been identified and used as a base of analysis. Following the determination of the most popular keywords, allinanchor and allintitle search has been conducted and the first ten results of the searches have been collected to identify the companies with the most significant web presence among the nursery shops. Finally, Link Profiling has been performed where the essential goal was to understand to what extent other companies' link structure is different that the base company's backlinks. Significant difference has been found that distinguished the top three companies ranking in the allinanchor and allintitle search. The top three companies, „Mothercare”, „Mamas and Papas” and „Kiddicare” maintained significantly better metrics regarding domain and page authority on the main landing pages, the average number of outbound links for link portfolio metric and in number of backlinks. These companies also ranked among the highest in page authority distribution and followed external linking.

Inbound marketing in practice. Case study: Lainaaja.fi

The general purpose of the thesis was to describe and explain the particularities of inbound marketing methods and the key advantages of those methods. Inbound marketing can be narrowed down to a set of marketing strategies and techniques focused on pulling prospects towards a business and its products on the Internet by producing useful and relevant content to prospects. The main inbound marketing methods and channels were identified as blogging, content publishing, search engine optimization and social media. The best way to utilise these methods is producing great content that should cover subjects that interest the target group, which is usually a composition of buyers, existing customers and influencers, such as analysts and media The study revealed increase in Lainaaja.fi traffic and referral traffic sources that was firmly confirmed as statistically significant, while number of backlinks and SERP placement were clearly positively correlated, but not statistically significant. The number of new registered users along with new loan applicants and deposits did not show correlation with increased content producing. The conclusion of the study shows inbound marketing campaign clearly increasing website traffic and plausible help on getting better search engine results compared to control period. Implications are clear; inbound marketing is an activity that every business should consider implementing. But just producing content online is not enough; equal amount of work should be put into turning the visitors into customers. Further studies are recommended on using inbound marketing combined with monitoring of landing pages and conversion optimization to incoming visitors.

Elasticsearch as a new search engine for Invenio and more

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Search engine liability for autocomplete suggestions: personality, privacy and the power of the algorithm

This article is concerned with the liability of search engines for algorithmically produced search suggestions, such as through Google’s ‘autocomplete’ function. Liability in this context may arise when automatically generated associations have an offensive or defamatory meaning, or may even induce infringement of intellectual property rights. The increasing number of cases that have been brought before courts all over the world puts forward questions on the conflict of fundamental freedoms of speech and access to information on the one hand, and personality rights of individuals— under a broader right of informational self-determination—on the other. In the light of the recent judgment of the Court of Justice of the European Union (EU) in Google Spain v AEPD, this article concludes that many requests for removal of suggestions including private individuals’ information will be successful on the basis of EU data protection law, even absent prejudice to the person concerned.