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Exact solution of time–cost trade-off problem (TCTP) by the state-of-the-art meta-heuristic algorithms can be obtained for small- and medium-scale problems, while satisfactory results cannot be obtained for large construction projects. In this study, a hybrid heuristic meta-heuristic algorithm that adapts the search domain is developed to solve the large-scale discrete TCTP more efficiently.

Minimum cost slope–based heuristic network analysis algorithm (NAA), which eliminates the unfeasible search domain, is embedded into differential evolution meta-heuristic algorithm. Heuristic NAA narrows the search domain at the initial phase of the optimization. Moreover, activities with float durations higher than the predetermined threshold value are eliminated and then the meta-heuristic algorithm starts and searches the global optimum through the narrowed search space. However, narrowing the search space may increase the probability of obtaining a local optimum. Therefore, adaptive search domain approach is employed to make reintroduction of the eliminated activities to the design variable set possible, which reduces the possibility of converging into local minima.

The developed algorithm is compared with plain meta-heuristic algorithm with two separate analyses. In the first analysis, both algorithms have the same computational demand, and in the latter analysis, the meta-heuristic algorithm has fivefold computational demand. The tests on case study problems reveal that the developed algorithm presents lower total project costs according to the dependent t-test for paired samples with α = 0.0005.

In this study, TCTP is solved without considering quality or restrictions on the resources.

The proposed method enables to adapt the number of parameters, that is, the search domain and provides the opportunity of obtaining significant improvements on the meta-heuristic algorithms for other engineering optimization problems, which is the theoretical contribution of this study. The proposed approach reduces the total construction cost of the large-scale projects, which can be the practical benefit of this study.

This paper aims to describe how approaches such as semantic based query rewritings and FRBR work entities composition could solve existing problems and improve the overall behavior of a mediated based meta‐search environment. Moreover, it aims to present meta‐Composer, which is a meta‐search engine without query failures that composes work level entities for display, as well as an autonomous open service for discovering substitutions of unsupported access points, in the context of the Z39.50 environment.

Semantic Access Point Network (SAPN) engine, which is a system for substitution of unsupported access points by exploiting semantic access point information from an RDFS description, was extended as a query rewriting system taking into account user preferences for recall and precision. Additionally, the Library of Congress FRBR display tool was extended to create, in the first place, MARC21, UNIMARC and MODS wrappers for the production of work‐expression‐manifestation identifiers, and, secondly, the composition of work clusters. Finally, pazpar2, the open source meta‐search engine was used as both the middleware and the client platform for the integration of all the above components and the development of meta‐Composer.

Consistent extension of the meta‐search search functionality is possible from the lowest common denominator of the supported access points through semantic based query rewritings. Furthermore, enabling query specificity, which restricts the resulting records, could really improve the overall performance of the system and allow for more space for other extensions. Work centric result presentation gives a more compact and coherent view to the user compared to the typical record‐based de‐duplicated display.

The technical limitation for retrieving all the results from all sources, especially for large result sets, indicates the need for further research for the development of heuristics in order to find the best sources for enriching the results by unique work clusters. The absence of tools, such as authority files, limits the accuracy of the FRBRization process and the discovery of correlations between related works.

Consistent meta‐search services require widespread use of international metadata standards and communication protocols.

The SAPN technology enforces implicitly the semantic interoperability in the context of the Z39.50 protocol. meta‐Composer is an open service which offers meta‐search within valuable sources world wide and it also provides the potential to evaluate new services. The SAPN open service gives the ability to any other mediator or client, to extend and improve consistently its search functionality, in the same context and by using web services technology.

No study has investigated the effects of different parameters on publication bias in meta-analyses using a machine learning approach. Therefore, this study aims to evaluate the impact of various factors on publication bias in meta-analyses.

An electronic questionnaire was created according to some factors extracted from the Cochrane Handbook and AMSTAR-2 tool to identify factors affecting publication bias. Twelve experts were consulted to determine their opinion on the importance of each factor. Each component was evaluated based on its content validity ratio (CVR). In total, 616 meta-analyses comprising 1893 outcomes from PubMed that assessed the presence of publication bias in their reported outcomes were randomly selected to extract their data. The multilayer perceptron (MLP) technique was used in IBM SPSS Modeler 18.0 to construct a prediction model. 70, 15 and 15% of the data were used for the model's training, testing and validation partitions.

There was a publication bias in 968 (51.14%) outcomes. The established model had an accuracy rate of 86.1%, and all pre-selected nine variables were included in the model. The results showed that the number of databases searched was the most important predictive variable (0.26), followed by the number of searches in the grey literature (0.24), search in Medline (0.17) and advanced search with numerous operators (0.13).

The results of this study can help clinical researchers minimize publication bias in their studies, leading to improved evidence-based medicine.

To the best of the author’s knowledge, this is the first study to model publication bias using machine learning.

To explore the impact of using metadata in finding and ranking web pages through search engines.

The study has been divided into two phases. In phase one, the use of metadata schemes and the impact of overlapped documents have been examined by employing the usability technique. Phase two examined the impact of adding metadata elements to web pages in their original rank order, using the experimental method. This study focuses on indexing web pages using metadata and its impact on search engine's rankings.

Meta tags are more widely used than Dublin Core. The overlapped pages tend to include metadata. The second phase shows that by adding metadata elements to web pages, it raises its rank order. However, this depends on the quality of the description and the metadata schemes. The study shows no great difference in page ranking between adding meta tags and Dublin Core.

To maximize the impact of metadata, more attention should be given to keyword and descriptive fields.

The hypothetical relationship between overlapped pages and the inclusion of metadata and indexing by search engines had not been previously examined.

Search engines are used to locate information on the Web, but they cannot always adequately meet the information needs of users. Some schemes have been developed to solve this problem and meta‐tags are one of them. This article provides a comprehensive definition of meta‐tags and explains their function. Then, the possible attributes of meta‐tags and the most important meta‐tags are introduced in detail. It concludes that, although the meta‐tag has shortcomings, as do other schemes of information organizing, it can help improve the retrievability of information on the Web, and should be utilised by Web masters and search engine designers.

The purpose of this paper was to explore the ways travel intermediaries (online travel agencies (OTAs) and travel meta sites) used throughout the distribution value chain engaged in relationships with travel suppliers.

The multiple‐case study approach is suitable in examining contemporary events in their natural context. A commonly reported strength of the case study approach in that a variety of evidence can be used to investigate the subject matter. The data evidence gathered for this paper came from field study interviews and document analysis.

The results show that the relationship structure has an impact on the type of contractual agreement OTAs and meta sites have with travel suppliers and with each other.

These results can be used by top‐level executives involved in online travel as they research and test how to best craft their relationship and formal or informal agreements with their suppliers, affiliates, and other entities with which they choose to work.

Partnerships between travel suppliers and meta search engines could threaten travel agencies and allow travel suppliers a viable means to bypass agencies all together and maintain more control in both the transaction, the relationship building process with customers, and, ultimately, ownership of customers.

Based upon the current state, it is clear that the distribution landscape is in state of flux. Travel meta search engines are gaining traction, both in terms of market share and financial backing. Kayak's recent acquisition of SideStep helps to provide strength to Kayak and will likely be the catalyst for other mergers in due time. All of the major players are jockeying for position. There will likely be consolidation and more new entrants. To remain relevant, one must actively monitor this space, continue to keep abreast of developments as they unfold, and innovate. Most importantly, one must provide unmatched value to win customer loyalty and gain market share.

A reproductive plan is a type of adaptive procedure devised by Holland which embodies many principles found in the adaptation of natural systems through evolution. This study develops a reproductive meta‐plan, an adaptive procedure that controls the modification of parameter values in a reproductive plan. After a brief review of Holland's formalization of reproductive plans, a non‐reproductive meta‐plan devised by Cavicchio is discussed. In response to some of the limitations of Cavicchio's approach, a reproductive meta‐plan is developed. Experiments with computer implementations of both meta‐plans show improvement in a reproductive plan's utility gain when the reproductive meta‐plan is used.

This paper reports the findings of a major study examining the overlap among results retrieved by three major web search engines. The goal of the research was to: measure the overlap across three major web search engines on the first results page overlap (i.e. share the same results) and the differences across a wide range of user defined search terms; determine the differences in the first page of search results and their rankings (each web search engine's view of the most relevant content) across single‐source web search engines, including both sponsored and non‐sponsored results; and measure the degree to which a meta‐search web engine, such as Dogpile.com, provides searchers with the most highly ranked search results from three major single source web search engines.

The authors collected 10,316 random Dogpile.com queries and ran an overlap algorithm using the URL for each result by query. The overlap of first result page search for each query was then summarized across all 10,316 to determine the overall overlap metrics. For a given query, the URL of each result for each engine was retrieved from the database.

The percent of total results unique retrieved by only one of the three major web search engines was 85 percent, retrieved by two web search engines was 12 percent, and retrieved by all three web search engines was 3 percent. This small level of overlap reflects major differences in web search engines retrieval and ranking results.

This study provides an important contribution to the web research literature. The findings point to the value of meta‐search engines in web retrieval to overcome the biases of single search engines.

The results of this research can inform people and organizations that seek to use the web as part of their information seeking efforts, and the design of web search engines.

This research is a large investigation into web search engine overlap using real data from a major web meta‐search engine and single web search engines that sheds light on the uniqueness of top results retrieved by web search engines.

This paper describes an investigation of 20 different meta‐search engines. Their features were characterised and classified into six distinct categories based on their functionality and use. The most used features and unique features were specified and explained in detail. The findings of this study will benefit both meta‐search‐engine developers and ordinary search users.

This study evaluated two different types of online information retrieval (IR) systems: online databases and Web search engines, in terms of user generated criteria. It also compares four types of Web search engines: directories, search engines, meta‐search engines, and specialized search engines. The results show that three elements are essential to users in the evaluation of online IR systems: interface design, system performance and collection coverage. While participants preferred the ease of use and intuitive interfaces of Web search engines, they also liked the credible and useful information offered by online databases. Based on the discussion of advantages and problems of online databases and Web search engines, implications of for the design of IR systems are further suggested.