Compliment de les directrius DRIVER dels repositoris cooperatius RACO, RECERCAT i TDX

Aquest informe ha estat elaborat per encàrrec del Consorci de Biblioteques Universitàries de Catalunya (CBUC). El seu objectiu és comprovar si des del punt de vista tècnic, els repositoris cooperatius que el CBUC coordina juntament amb el Centre de Supercomputació de Catalunya (CESCA), es poden integrar dins la infrastructura DRIVER.

Driver scheduling problem modelling

The Drivers Scheduling Problem (DSP) consists of selecting a set of duties for vehicle drivers, for example buses, trains, plane or boat drivers or pilots, for the transportation of passengers or goods. This is a complex problem because it involves several constraints related to labour and company rules and can also present different evaluation criteria and objectives. Being able to develop an adequate model for this problem that can represent the real problem as close as possible is an important research area.The main objective of this research work is to present new mathematical models to the DSP problem that represent all the complexity of the drivers scheduling problem, and also demonstrate that the solutions of these models can be easily implemented in real situations. This issue has been recognized by several authors and as important problem in Public Transportation. The most well-known and general formulation for the DSP is a Set Partition/Set Covering Model (SPP/SCP). However, to a large extend these models simplify some of the specific business aspects and issues of real problems. This makes it difficult to use these models as automatic planning systems because the schedules obtained must be modified manually to be implemented in real situations. Based on extensive passenger transportation experience in bus companies in Portugal, we propose new alternative models to formulate the DSP problem. These models are also based on Set Partitioning/Covering Models; however, they take into account the bus operator issues and the perspective opinions and environment of the user.We follow the steps of the Operations Research Methodology which consist of: Identify the Problem; Understand the System; Formulate a Mathematical Model; Verify the Model; Select the Best Alternative; Present the Results of theAnalysis and Implement and Evaluate. All the processes are done with close participation and involvement of the final users from different transportation companies. The planner s opinion and main criticisms are used to improve the proposed model in a continuous enrichment process. The final objective is to have a model that can be incorporated into an information system to be used as an automatic tool to produce driver schedules. Therefore, the criteria for evaluating the models is the capacity to generate real and useful schedules that can be implemented without many manual adjustments or modifications. We have considered the following as measures of the quality of the model: simplicity, solution quality and applicability. We tested the alternative models with a set of real data obtained from several different transportation companies and analyzed the optimal schedules obtained with respect to the applicability of the solution to the real situation. To do this, the schedules were analyzed by the planners to determine their quality and applicability. The main result of this work is the proposition of new mathematical models for the DSP that better represent the realities of the passenger transportation operators and lead to better schedules that can be implemented directly in real situations.

Metaheuristics for the bus-driver scheduling problem

We present new metaheuristics for solving real crew scheduling problemsin a public transportation bus company. Since the crews of thesecompanies are drivers, we will designate the problem by the bus-driverscheduling problem. Crew scheduling problems are well known and severalmathematical programming based techniques have been proposed to solvethem, in particular using the set-covering formulation. However, inpractice, there exists the need for improvement in terms of computationalefficiency and capacity of solving large-scale instances. Moreover, thereal bus-driver scheduling problems that we consider can present variantaspects of the set covering, as for example a different objectivefunction, implying that alternative solutions methods have to bedeveloped. We propose metaheuristics based on the following approaches:GRASP (greedy randomized adaptive search procedure), tabu search andgenetic algorithms. These metaheuristics also present some innovationfeatures based on and genetic algorithms. These metaheuristics alsopresent some innovation features based on the structure of the crewscheduling problem, that guide the search efficiently and able them tofind good solutions. Some of these new features can also be applied inthe development of heuristics to other combinatorial optimizationproblems. A summary of computational results with real-data problems ispresented.

Open licensing's impact on higher education resources colombian and catalan approaches

A new initiative has sprung on the path created by the Open Access (OA) movement: Open Education (OE). The initiative's aim is to open up all educational resources at all learning levels. In order to achieve this goal, several international institutions, like UNESCO and the OECD, have published reports, surveys and documents to help educational institutions in this endeavor. This global initiative needs a legal framework; as a result, efforts thus far have usually resorted to Open Licensing (OL), especially Creative Commons (CC) licensing. In fact, as a response to this new movement, Creative Commons launched a new program, ccLearn , which recognizes open licensing's impact on education and directly supports the idea of open educational resources (OER). However, there still remain a good amount of open questions: What is happening locally with OL in higher education? How are educational institutions receiving the initiative? How is it that the OL initiative relates to educational resources? Are there local examples of open educational resources (OER)? How do these local instances incorporate CC into their educational frameworks?. To this effect, this analysis aims to focus on the legal approach and specifically on the way the educational sector is using open licenses outside the English speaking world. It will do so by looking at the current situation in two specific scenarios, the Colombian and the Catalan experiences with open educational projects at the higher education level.

Knowledge Licensing in a Model of R&D-driven Endogenous Growth

In this paper I present an endogenous growth model where the engine of growth is in-house R&D performed by high-tech firms. I model knowledge (patent) licensing among high-tech firms. I show that if there is knowledge licensing, high-tech firms innovate more and economic growth is higher than in cases when there are knowledge spillovers or there is no exchange of knowledge among high-tech firms. However, in case when there is knowledge licensing the number of high-tech firms is lower than in cases when there are knowledge spillovers or there is no exchange of knowledge.

Knowledge Licensing in a Model of R&D-driven Endogenous Growth

In this paper I present an endogenous growth model where the engine of growth is in-house R&D performed by high-tech firms. I model knowledge (patent) licensing among high-tech firms. I show that if there is knowledge licensing, high-tech firms innovate more and economic growth is higher than in cases when there are knowledge spillovers or there is no exchange of knowledge among high-tech firms. However, in case when there is knowledge licensing the number of high-tech firms is lower than in cases when there are knowledge spillovers or there is no exchange of knowledge.

Licensing Review in R+D Projects

FOSS packages are becoming ever more present in R&D projects carried out a variety of entities, including large corporations. I will focus on how legal risks associated with the use of FOSS licenses can be assessed and discuss measures directed to risk mitigation.

Driver costs in small firms: Empirical analysis for farms

The agricultural sector has always been characterized by a predominance of small firms. International competition and the consequent need for restraining costs are permanent challenges for farms. This paper performs an empirical investigation of cost behavior in agriculture using panel data analysis. Our results show that transactions caused by complexity influence farm costs with opposite effects for specific and indirect costs. While transactions allow economies of scale in specific costs, they significantly increase indirect costs. However, the main driver for farm costs is volume. In addition, important differences exist for small and big farms, since transactional variables significantly influence the former but not the latter. While sophisticated management tools, such ABC, could provide only limited complementary useful information but no essential allocation bases for farms, they seem inappropriate for small farms

Driver costs in small firms: Empirical analysis for farms

The agricultural sector has always been characterized by a predominance of small firms. International competition and the consequent need for restraining costs are permanent challenges for farms. This paper performs an empirical investigation of cost behavior in agriculture using panel data analysis. Our results show that transactions caused by complexity influence farm costs with opposite effects for specific and indirect costs. While transactions allow economies of scale in specific costs, they significantly increase indirect costs. However, the main driver for farm costs is volume. In addition, important differences exist for small and big farms, since transactional variables significantly influence the former but not the latter. While sophisticated management tools, such ABC, could provide only limited complementary useful information but no essential allocation bases for farms, they seem inappropriate for small farms