1,720,954 research outputs found
Optimalisering av ressursallokering ved Moss Havn
Full text linkDenne oppgaven tar for seg ressursallokeringsproblemet ved Moss Havn, med hovedfokus på bemanning og utstyr som inngår i containerhåndteringen. Oppgavens mål er å undersøke hvordan ressursallokeringen ved Moss Havn kan optimaliseres for å redusere flaskehalser, sikre effektiv containerhåndtering og forbedre arbeidsflyten. For å analysere dette er det utviklet en mixed integer linear programming-modell som tildeler trucker til ulike operasjoner. Modellen er ment å fungere som et beslutningsstøtteverktøy for planlegging og optimalisering av truckfordelingen ved havnen.
Oppgaven er gjennomført i samarbeid med Moss Havn KF og Westport AS. Grunnlaget for oppgaven kommer fra både kvalitative og kvantitative data innsamlet gjennom dialog, intervjuer og analyse av tilsendt driftsdata. Oppgaven baseres på havnens eksisterende prosesser spesielt knyttet til lasting, lossing og intern transport, og vurderer hvordan ulike trucktildelinger og prioriteringer påvirker kapasitet og gjennomstrømning av containere.
Optimaliseringsmodellen er utviklet i Python, basert på reelle data fra Moss Havn og Westport. Formålet med modellen er å minimere opphopning av containere ved å tildele trucker til konkurrerende aktiviteter. Modellen benyttes til å simulere ulike scenarier for ressursbruk ved havnen. Resultatene viser at det er stort potensial for effektivisering spesielt innenfor bedre planlegging og smartere fordeling av trucker.
Konklusjonen er at en bedre tilnærming til ressursallokering spesielt knyttet til truckallokering kan gi havnen økt driftseffektivitet samt reduserte ventetider for både lastebiler og skip. Dette legger til grunn for kostnadsbesparelser knyttet til overtid og bedre kapasitet til å håndtere fremtidig vekst i containertrafikken.This thesis addresses the resource allocation problem at Moss Havn, with a main focus on staffing and equipment involved in container handling. The aim of the thesis is to investigate how resource allocation at Moss Havn can be optimized to reduce bottlenecks, ensure efficient container handling and improve workflow. To analyze this, a mixed integer linear programming model has been developed that allocates the reach stackers to different operations. The model is intended to function as a decision support tool for planning and optimizing reach stacker distribution at the port.
The thesis has been carried out in collaboration with Moss Havn KF and Westport AS. The basis for the thesis comes from both qualitative and quantitative data collected through dialogue, interviews and analysis of submitted operational data. The thesis is based on the port's existing processes, especially related to loading, unloading and internal transport, and assesses how different truck allocations and priorities affect capacity and throughput of containers.
The optimization model has been developed in Python, based on real data from Moss Havn and Westport. The purpose of the model is to minimize the accumulation of containers by allocating the reach stackers to competing activities. The model is used to simulate different scenarios for resource use at the port. The results show that there is great potential for efficiency improvements, especially in better planning and smarter distribution of the reach stackers.
The conclusion is that a better approach to resource allocation, especially related to reach stacker allocation, can provide the port with increased operational efficiency and reduced waiting times for both trucks and ships. This provides the basis for cost savings related to overtime and better capacity to handle future growth in container traffic
Optimalisering av ressursallokering ved Moss Havn
Full text linkDenne oppgaven tar for seg ressursallokeringsproblemet ved Moss Havn, med hovedfokus på bemanning og utstyr som inngår i containerhåndteringen. Oppgavens mål er å undersøke hvordan ressursallokeringen ved Moss Havn kan optimaliseres for å redusere flaskehalser, sikre effektiv containerhåndtering og forbedre arbeidsflyten. For å analysere dette er det utviklet en mixed integer linear programming-modell som tildeler trucker til ulike operasjoner. Modellen er ment å fungere som et beslutningsstøtteverktøy for planlegging og optimalisering av truckfordelingen ved havnen.
Oppgaven er gjennomført i samarbeid med Moss Havn KF og Westport AS. Grunnlaget for oppgaven kommer fra både kvalitative og kvantitative data innsamlet gjennom dialog, intervjuer og analyse av tilsendt driftsdata. Oppgaven baseres på havnens eksisterende prosesser spesielt knyttet til lasting, lossing og intern transport, og vurderer hvordan ulike trucktildelinger og prioriteringer påvirker kapasitet og gjennomstrømning av containere.
Optimaliseringsmodellen er utviklet i Python, basert på reelle data fra Moss Havn og Westport. Formålet med modellen er å minimere opphopning av containere ved å tildele trucker til konkurrerende aktiviteter. Modellen benyttes til å simulere ulike scenarier for ressursbruk ved havnen. Resultatene viser at det er stort potensial for effektivisering spesielt innenfor bedre planlegging og smartere fordeling av trucker.
Konklusjonen er at en bedre tilnærming til ressursallokering spesielt knyttet til truckallokering kan gi havnen økt driftseffektivitet samt reduserte ventetider for både lastebiler og skip. Dette legger til grunn for kostnadsbesparelser knyttet til overtid og bedre kapasitet til å håndtere fremtidig vekst i containertrafikken.This thesis addresses the resource allocation problem at Moss Havn, with a main focus on staffing and equipment involved in container handling. The aim of the thesis is to investigate how resource allocation at Moss Havn can be optimized to reduce bottlenecks, ensure efficient container handling and improve workflow. To analyze this, a mixed integer linear programming model has been developed that allocates the reach stackers to different operations. The model is intended to function as a decision support tool for planning and optimizing reach stacker distribution at the port.
The thesis has been carried out in collaboration with Moss Havn KF and Westport AS. The basis for the thesis comes from both qualitative and quantitative data collected through dialogue, interviews and analysis of submitted operational data. The thesis is based on the port's existing processes, especially related to loading, unloading and internal transport, and assesses how different truck allocations and priorities affect capacity and throughput of containers.
The optimization model has been developed in Python, based on real data from Moss Havn and Westport. The purpose of the model is to minimize the accumulation of containers by allocating the reach stackers to competing activities. The model is used to simulate different scenarios for resource use at the port. The results show that there is great potential for efficiency improvements, especially in better planning and smarter distribution of the reach stackers.
The conclusion is that a better approach to resource allocation, especially related to reach stacker allocation, can provide the port with increased operational efficiency and reduced waiting times for both trucks and ships. This provides the basis for cost savings related to overtime and better capacity to handle future growth in container traffic
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
