A genetic algorithm for the resource constrained multi-project scheduling problem

This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Project scheduling using a competitive genetic algorithm

- The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm

Remote experimentation network - yielding an inter-university peer-to-peer e-service

The goal of this paper is to discuss the benefits and challenges of yielding an inter-continental network of remote laboratories supported and used by both European and Latin American Institutions of Higher Education. Since remote experimentation, understood as the ability to carry out real-world experiments through a simple Web browser, is already a proven solution for the educational community as a supplement to on-site practical lab work (and in some cases, namely for distance learning courses, a replacement to that work), the purpose is not to discuss its technical, pedagogical, or economical strengths, but rather to raise and try to answer some questions about the underlying benefits and challenges of establishing a peer-to-peer network of remote labs. Ultimately, we regard such a network as a constructive mechanism to help students gain the working and social skills often valued by multinational/global companies, while also providing awareness of local cultural aspects.

A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problem

This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

A two-level genetic algorithm for the multi-mode resource-constrained project scheduling problem

This paper presents a genetic algorithm for the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme by introducing an improvement procedure. It is evaluated the quality of the schedule and present detailed comparative computational results for the MRCPSP, which reveal that this approach is a competitive algorithm.

Privatization and entry of a foreign firm with demand uncertainty

We investigate the effects of trade with a foreign firm and privatization of the domestic pubUc firm on an incentive for the domestic firm to reduce costs by undertaking R&D investment, under demand uncertainty. We suppose that the domestic firm is less efficient than the foreign firm. However, the domestic firm can lower its marginal costs by conducting cost-reducing R&D investment. We examine the impacts of entry of a foreign firm, and the effects of demand uncertainty, on decisions upon cost-reducing R&D investment by the domestic firm and how these affect the domestic welfare.

Cournot competition between a non-profit firm and a for-profit firm with uncertainty

In this paper, we consider a Cournot competition between a nonprofit firm and a for-profit firm in a homogeneous goods market, with uncertain demand. Given an asymmetric tax schedule, we compute explicitly the Bayesian-Nash equilibrium. Furthermore, we analyze the effects of the tax rate and the degree of altruistic preference on market equilibrium outcomes.

TRAILER project overview: tagging, recognition and acknowledgment of informal learning experiences

The evolution of new technology and its increasing use, have for some years been making the existence of informal learning more and more transparent, especially among young and older adults in both Higher Education and workplace contexts. However, the nature of formal and non-formal, course-based, approaches to learning has made it hard to accommodate these informal processes satisfactorily, and although technology bring us near to the solution, it has not yet achieved. TRAILER project aims to address this problem by developing a tool for the management of competences and skills acquired through informal learning experiences, both from the perspective of the user and the institution or company. This paper describes the research and development main lines of this project.

A random key based genetic algorithm for the resource constrained project scheduling problem

This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Project, modelling and simulation of air stripping columns for the treatment of groundwater contaminated with volatile organic compounds

Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for the column design for any particular type of packing and contaminant avoiding the necessity of a pre-defined diameter used in the classical approach. It also renders unnecessary the employment of the graphical Eckert generalized correlation for pressure drop estimates. The hydraulic features are previously chosen as a project criterion and only afterwards the mass transfer phenomena are incorporated, in opposition to conventional approach. The design procedure was translated into a convenient algorithm using C++ as programming language. A column was built in order to test the models used either in the design or in the simulation of the column performance. The experiments were fulfilled using a solution of chloroform in distilled water. Another model was built to simulate the operational performance of the column, both in steady state and in transient conditions. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting system of ODE can be solved, allowing for the calculation of the concentration profile in both phases inside the column. In transient state the system of PDE was numerically solved by finite differences, after a previous linearization.

Enhancing informal learning recognition through TRAILER project

International Workshop on solutions that Enhance Informal LEarning Recognition – WEILER 2013

Institutional factors governing the deployment of remote experiments: lessons from the rexnet project

Remote labs offer many unique advantages to students as they provide opportunities to access experiments and learning scenarios that would be otherwise unavailable. At the same time, however, these opportunities introduce real challenges to the institutions hosting the remote labs. This paper draws on the experiences of the REXNET project consortium to expose a number of these issues as a means of furthering the debate on the value of remote labs and the best practices in deploying them. The paper presents a brief outline of the various types of remote lab scenarios that might be deployed. It then describes the key human and technological actors that have an interest in or are intrinsic to a remote lab instance, with a description of the role of each actor and their interest. Some relationships between these various actors are then discussed with some factors that might influence those relationships. Finally some general issues are briefly described.

The European Project Semester at ISEP: Learning to Learn Engineering

The European Project Semester at ISEP (EPS@ISEP) is a one semester project-based learning programme addressed to engineering students from diverse scientific backgrounds and nationalities. The students, organized in multicultural teams, are challenged to solve real world multidisciplinary problems, accounting for 30 ECTU. The EPS package, although focused on project development (20 ECTU), includes a series of complementary seminars aimed at fostering soft, project-related and engineering transversal skills (10 ECTU). This paper presents the study plan, resources, operation and results of the EPS@ISEP that was created in 2011 to apply the best engineering education practices and promote the internationalization of ISEP. The results show that the EPS@ISEP students acquire during one semester the scientific, technical and soft competences necessary to propose, design and implement a solution for a multidisciplinary problem.