OPTIMIZING PROJECT TIME-COST-QUALITY BY USING GENETIC ALGORITHMS

Project management causes the problem of efficient resource assignment, activity, time constraints and relationships between activities. Traditional scheduling methods like CPM and PERT are incomplete tools to use in practice because they do not consider constraints regarding resources and cannot be realistic as they consider infinite resources. Optimization of project time-costs-quality is very complex and can be achieved by using meta-heuristic methods as Genetic Algorithms, Ant Algorithm, Tabu Search. In this article we study the state of the art in this domain, define the optimization problem we want to solve and propose some improvements for a genetic algorithm, starting from GENOCOP I (Genetic Algorithm for Numerical Optimizations of Constrained Problems) developed by Michalewicz and Janikow[12], later improved to GENOCOP V (Suzuki [9]).planning and scheduling, time-costs trade-off problem, genetic algorithms

CONTRIBUTIONS TO MULTI-AGENT SYSTEMS IMPLEMENTATION FOR PROJECT SCHEDULING

Increasing project complexity makes scheduling problems more difficult to solve and requires more versatile algorithms. Two different approaches for the project scheduling optimization could be considered: TCPSP (Time-Constrained Project Scheduling), and RCPSP (Resource-Constrained Project Scheduling). In this paper we study thepossibility to apply Multi-Agent Systems (MAS) for these scheduling problems regarding different fitness functions. Wesearch for strengths and weaknesses of MAS as a prerequisite study for a further implementation of the TCSP on a specific MAS platform.multi-agent systems, scheduling, project management, planning

A multi-agent system with application in project scheduling

The new economic and social dynamics increase project complexity and makes scheduling problems more difficult, therefore scheduling requires more versatile solutions as Multi Agent Systems (MAS). In this paper the authors analyze the implementation of a Multi-Agent System (MAS) considering two scheduling problems: TCPSP (Time-Constrained Project Scheduling), and RCPSP (Resource-Constrained Project Scheduling). The authors propose an improved BDI (Beliefs, Desires, and Intentions) model and present the first the MAS implementation results in JADE platform.multi-agent architecture, scheduling, project management, BDI architecture, JADE.

Distributed Research Project Scheduling Based on Multi-Agent Methods

Different project planning and scheduling approaches have been developed. The Operational Research (OR) provides two major planning techniques: CPM (Critical Path Method) and PERT (Program Evaluation and Review Technique). Due to projects complexity and difficulty to use classical methods, new approaches were developed. Artificial Intelligence (AI) initially promoted the automatic planner concept, but model-based planning and scheduling methods emerged later on. The paper adresses the project scheduling optimization problem, when projects are seen as Complex Adaptive Systems (CAS). Taken into consideration two different approaches for project scheduling optimization: TCPSP (Time- Constrained Project Scheduling) and RCPSP (Resource-Constrained Project Scheduling), the paper focuses on a multiagent implementation in MATLAB for TCSP. Using the research project as a case study, the paper includes a comparison between two multi-agent methods: Genetic Algorithm (GA) and Ant Colony Algorithm (ACO)

COVID-19 Vaccine Does Not Increase the Risk of Disease Flare-Ups among Patients with Autoimmune and Immune-Mediated Diseases

Background: Reports describing post-vaccine autoimmune phenomena, in previously healthy individuals, increased the concerns regarding the risk of disease flare-ups in patients with immune diseases. We aimed to assess the potential risk of disease flare-up, after receiving the COVID-19 (Coronavirus disease 2019) vaccine, during a follow-up period of 6 months. Methods: We performed a prospective cohort study, enrolling the patients with autoimmune- and immune-mediated diseases who voluntarily completed our questionnaire, both online and during hospital evaluations. Based on their decision to receive the vaccine, the patients were divided into two groups (vaccinated and non-vaccinated). Participants who chose not to receive the vaccine served as a control group in terms of flare-ups. Results: A total of 623 patients, 416 vaccinated and 207 non-vaccinated, were included in the study during hospital evaluations (222/623) and after online (401/623) enrolment. There was no difference concerning the risk of flare-up between vaccinated and non-vaccinated patients (1.16, versus 1.72 flare-ups/100 patients-months, p = 0.245). The flare-ups were associated with having more than one immune disease, and with a previous flare-up during the past year. Conclusions: We did not find an increased risk of flare-up following COVID-19 vaccination in patients with autoimmune-/immune-mediated diseases, after a median follow-up of 5.9 months. According to our results, there should not be an obvious reason for vaccine hesitancy among this category of patients

COVID-19 Impact and Vaccination Willingness among Romanian Patients with Autoimmune/Immune-Mediated Diseases

Background: During the COVID-19 pandemic, patients with immune diseases are a vulnerable population. We aimed to evaluate their access to medical care, as well as their awareness and willingness to obtain the vaccine after a year of the SARS-CoV-2 pandemic. Methods: A cross-sectional, multicenter study was conducted on a questionnaire basis, handled both online as well as in person. Results: 651 patients with autoimmune or immune mediated diseases were enrolled. More than half (339/641 [53%]) reported difficulties in obtaining medical care throughout the pandemic and 135/651 ([21%]) of them were confirmed with COVID-19; 442/651, ([68%]) expressed their willingness to be vaccinated against SARS-CoV-2. The factors associated with an increased probability of vaccination were the male gender (OR = 2.01, CI95% 1.2–3.7, p = 0.001), the patient’s opinion that she/he was well informed (OR = 3.2, CI 95% 2.1–6.01, p < 0.001), physician’s advice (OR = 2.1, CI 95% 1.3–3.5, p < 0.001), and flu vaccination in the past (OR = 1.5, CI 95% 1.1–2.3, p < 0.001), while those associated with a decreased probability of vaccination were COVID-19 disease in the past medical history (OR = 0.7, CI 95% 0.3-0.95, p = 0.02), and the opinion that patients with autoimmune diseases are at increased risk for adverse reactions (OR = 0.7, CI95% 0.53–0.89, p = 0.001). Conclusions: Given the fact that considering themselves informed regarding vaccination is the most important factor in order to be immunized against SARS-CoV-2, effective information campaigns would substantially increase willingness