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.

PERFORMANCE EVALUATION OF RESOURCE-AWARE BUSINESS PROCESSES USING STOCHASTIC AUTOMATA NETWORKS

In this work, we study the performance evaluation of resource-aware business process models. We define a new framework that allows the generation of analytical models for performance evaluation from business process models annotated with resource management information. This framework is composed of a new notation that allows the specification of resource management constraints and a method to convert a business process specification and its resource constraints into Stochastic Automata Networks (SANs). We show that the analysis of the generated SAN model provides several performance indices, such as average throughput of the system, average waiting time, average queues size, and utilization rate of resources. Using the BP2SAN tool - our implementation of the proposed framework - and a SAN solver (such as the PEPS tool) we show through a simple use-case how a business specialist with no skills in stochastic modeling can easily obtain performance indices that, in turn, can help to identify bottlenecks on the model, to perform workload characterization, to define the provisioning of resources, and to study other performance related aspects of the business process.

A serial scheme for minimizing the duration of resource-constrained projects within Microsoft Project

Microsoft Project is one of the most-widely used software packages for project management. For the scheduling of resource-constrained projects, the package applies a priority-based procedure using a specific schedule-generation scheme. This procedure performs relatively poorly when compared against other software packages or state-of-the-art methods for resource-constrained project scheduling. In Microsoft Project 2010, it is possible to work with schedules that are infeasible with respect to the precedence or the resource constraints. We propose a novel schedule-generation scheme that makes use of this possibility. Under this scheme, the project tasks are scheduled sequentially while taking into account all temporal and resource constraints that a user can define within Microsoft Project. The scheme can be implemented as a priority-rule based heuristic procedure. Our computational results for two real-world construction projects indicate that this procedure outperforms the built-in procedure of Microsoft Project

Online trendy topics detection in microblogs with selective user monitoring under cost constraints

As microblog services such as Twitter become a fast and convenient communication approach, identification of trendy topics in microblog services has great academic and business value. However detecting trendy topics is very challenging due to huge number of users and short-text posts in microblog diffusion networks. In this paper we introduce a trendy topics detection system under computation and communication resource constraints. In stark contrast to retrieving and processing the whole microblog contents, we develop an idea of selecting a small set of microblog users and processing their posts to achieve an overall acceptable trendy topic coverage, without exceeding resource budget for detection. We formulate the selection operation of these subset users as mixed-integer optimization problems, and develop heuristic algorithms to compute their approximate solutions. The proposed system is evaluated with real-time test data retrieved from Sina Weibo, the dominant microblog service provider in China. It's shown that by monitoring 500 out of 1.6 million microblog users and tracking their microposts (about 15,000 daily) with our system, nearly 65% trendy topics can be detected, while on average 5 hours earlier before they appear in Sina Weibo official trends.

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem. © 2013 Published by Elsevier Ltd.

Modelling the development of an online learning resource by health care professionals

The aim of this study was to model the process of development for an Online Learning Resource (OLR) by Health Care Professionals (HCPs) to meet lymphoedema-related educational needs, within an asset-based management context. Previous research has shown that HCPs have unmet educational needs in relation to lymphoedema but details on their specific nature or context were lacking. Against this background, the study was conducted in two distinct but complementary phases. In Phase 1, a national survey was conducted of HCPs predominantly in community, oncology and palliative care services, followed by focus group discussions with a sample of respondents. In Phase 2, lymphoedema specialists (LSs) used an action research approach to design and implement an OLR to meet the needs identified in Phase 1. Study findings were analysed using descriptive statistics (Phase 1), and framework, thematic and dialectic analysis to explore their potential to inform future service development and education theory. Unmet educational need was found to be specific to health care setting and professional group. These resulted in HCPs feeling poorly-equipped to diagnose and manage lymphoedema. Of concern, when identified, lymphoedema was sometimes buried for fear of overwhelming stretched services. An OLR was identified as a means of addressing the unmet educational needs. This was successfully developed and implemented with minimal additional resources. The process model created has the potential to inform contemporary leadership theory in asset-based management contexts. This doctoral research makes a timely contribution to leadership theory since the resource constraints underpinning much of the contribution has salience to current public services. The process model created has the potential to inform contemporary leadership theory in asset-based management contexts. Further study of a leadership style which incorporates cognisance of Cognitive Load Theory and Self-Determination Theory is suggested. In addition, the detailed reporting of process and how this facilitated learning for participants contributes to workplace education theory

The role of economic evaluation in mental health care

Objective: A consequence of the integration of psychiatry into acute and public health medicine is that psychiatrists are being asked to evaluate their services. There is pressure on mental health-care systems because it is recognized that funds should be directed where they can provide the best health outcomes, and also because there are resource constraints which limit our capacity to meet all demands for health care. This pressure can be responded to by evaluation which demonstrates the effectiveness and efficiency of psychiatric treatment. This paper seeks to remind psychiatrists of the fundamental principles of economic evaluation in the hope that these will enable psychiatrists to understand the methods used in evaluation and to work comfortably with evaluators. Method: The paper reviews the basic principles behind economic evaluation, illustrating these with reference to case studies. It describes: (i) the cost of the burden of illness and treatment, and how these costs are measured; (ii) the measurement of treatment outcomes, both as changes in health status and as resources saved; and (iii) the various types of economic evaluation, including cost-minimization, cost-effectiveness, cost-utility and cost-benefit analysis. Results: The advice in the paper provides psychiatrists with the necessary background to work closely with evaluators. A checklist of the critical questions to be addressed is provided as a guide for those undertaking economic evaluations. Conclusions: If psychiatrists are willing to learn the basic principles of economic evaluation and to apply these, they can respond to the challenges of evaluation.

Attitudes and practices of general practitioners in the diagnosis and management of attention-deficit/hyperactivity disorder

Objective: To assess understanding of, and actual and potential roles in management of attention-deficit/hyperactivity disorder (ADHD) among GPs. Methods: A cross-sectional questionnaire survey of Queensland GPs selected randomly from the Royal Australian College of General Practitioners directory of members was carried out. Main outcome measures were knowledge levels of ADHD, current management practices, referral patterns and self-perceived information and training needs. Results: Three hundred and ninety-nine GPs returned a completed questionnaire (response rate 76%). Roles identified by GPs were: the provisional diagnosis of ADHD and referral to specialist services for confirmation of the diagnosis and initiation of management; assistance with monitoring progress once a management plan was in place; education of the child and their family regarding the disorder; and liaison with the school where necessary. Perceived barriers to increased involvement of GPs were: time and resource constraints of general practice; concerns regarding abuse and addiction liability of prescription stimulants; complex diagnostic issues associated with childhood behavioural problems; and lack of training and education regarding ADHD. Conclusions: General practitioners identify a role for themselves in ADHD care that is largely supportive in nature and involves close liaison with specialist services.

Evidence and information for health policy: a decade of change

Over the past decade or so, there has been increasing demand for greater clarity about the major causes of disease and injury, how these differentially affect populations, and how they are changing. In part, this demand has been motivated by resource constraints and a realisation that better health is possible with more informed allocation of resources. At the same time, there has been a change in the way population health and its determinants are quantified, with a much closer integration of the quantitative population sciences (such as epidemiology, demography and health economics) to strengthen and broaden the evidence base for healthcare policy.

QoS-based surrogates selection and service proposal formulation in offloading environments

Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime.

Run-time monitoring approach for the shark kernel

Typically common embedded systems are designed with high resource constraints. Static designs are often chosen to address very specific use cases. On contrast, a dynamic design must be used if the system must supply a real-time service where the input may contain factors of indeterminism. Thus, adding new functionality on these systems is often accomplished by higher development time, tests and costs, since new functionality push the system complexity and dynamics to a higher level. Usually, these systems have to adapt themselves to evolving requirements and changing service requests. In this perspective, run-time monitoring of the system behaviour becomes an important requirement, allowing to dynamically capturing the actual scheduling progress and resource utilization. For this to succeed, operating systems need to expose their internal behaviour and state, making it available to the external applications, usually using a run-time monitoring mechanism. However, such mechanism can impose a burden in the system itself if not wisely used. In this paper we explore this problem and propose a framework, which is intended to provide this run-time mechanism whilst achieving code separation, run-time efficiency and flexibility for the final developer.

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.

A constructive technology assessment of stationary energy storage systems: prospective life cycle orientated analysis

Based on the presentation and discussion at the 3rd Winter School on Technology Assessment, December 2012, Universidade Nova de Lisboa (Portugal), Caparica Campus, PhD programme on Technology Assessment

Transgenic plant factories for the production of biopolymers and plateform chemicals

In the mid-to long-term, resource constraints will force society to cover a significant share of the future demand for fuels, materials and chemicals by renewable resources. This trend is already visible in the increasing conversion of carbohydrates and plant oils to fuels, chemicals, and polymers. In this perspective, we discuss current efforts and ideas to produce platform chemicals and polymers directly in transgenic plants.

Kansainvälinen markkinavalinta ohjelmistoalan mikroyrityksessä

Tutkielman tutkimusongelmana on, miten kansainvälinen kohdemarkkinoiden valinta pitäisi suorittaa ohjelmistoalan mikroyrityksessä. Tutkielma on kvalitatiivinen, yksittäinen tapaustutkimus. Teoriaosassa tutkimusongelmaa lähestytään tarkastelemalla kirjallisuutta, joka käsittelee kansainväliseen kohdemarkkinavalintaan vaikuttavia tekijöitä sekä olemassa olevia markkinavalintamalleja. Vanhojen mallien pohjalta kehitetään uusi käytännönläheinen ohjelmistoalan mikroyritykselle sopiva maavalintamalli. Kehitetty maavalintamalli koostuu eri vaiheista, joita ovat 1) sisäisten tekijöiden kartoittaminen, 2) alkukarsinta, 3) yrityksen kilpailukyvyn ja markkinoiden houkuttelevuuden mittaaminen matriisin avulla. Kehitettyä mallia sovelletaan tapausyritykseen tekemällä kansainvälinen markkinavalinta perustuen työpöytätutkimukseen, jossa käytetään Internetistä saatavaa sekundääridataa ja markkinatietoa. Työn lopussa esitetään markkinavalinnan tulokset ja toimenpidesuositukset yrityksen johdolle. Tutkimus osoittaa, että resurssipulasta huolimatta systemaattinen ja loogisesti etenevä maavalintaprosessi on mahdollista toteuttaa myös mikroyrityksessä. Ennalta määrätyt numeeriset rajat valintakriteereille mahdollistavat markkinoiden tarkastelun objektiivisuuden. Suurimpana haasteena ohjelmistoalan mikroyrityksen kansainvälisessä kohdemarkkinavalinnassa on yrityksen kilpailukyvyn mittaaminen eri markkinoilla. Tämäjohtuu osin ohjelmistoalan dynaamisesta luonteesta sekä kilpailija-analyysien subjektiivisuudesta.