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Author: search.filters.author.Dragan PamučarHas files: No

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    A green project scheduling with material ordering problem considering cost constraints and quality of materials
    (Emerald Publishing Limited, 2024-06-17)
    Purpose Integrating project scheduling and material ordering problems is vital in realistically estimating project cost and duration. Also, the quality level of materials is important as one of the key project success factors. Design/methodology/approach In this paper, a three-objective mathematical model is presented for green project scheduling with materials ordering problems considering rental resources. The first objective is to minimize the total cost of the project site and logistics. The second objective is to minimize the environmental impacts of producing materials and the third objective is to maximize the total quality of materials. Since costs trigger several challenges in projects, cost constraints are considered in this model for the first time and also the cost of delay in supplying of materials by the suppliers has been deducted from the project costs. Subsequently, the model was implemented in a real case and solved by the Lagrangian Relaxation algorithm as an exact method on GAMS software for model validation. Findings Based on sensitivity analysis of some parameters, the findings indicate that the cost constraint and lead time have considerable effects on the project duration. Also, integrating project scheduling and material ordering improves the robustness of the project schedule. Originality/value The primary contributions of the present research can be stated as follows: considering the cost constraints in the project scheduling with material ordering problem, incorporating the rental resources and taking the quality levels of materials as well as the environmental impacts into account.
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    An efficient intelligent intrusion detection system using fuzzy logic based on the Particle Swarm Optimization algorithm: A case study
    (IOS Press, 2025-04-01)
    This paper presents an intelligent intrusion detection system using fuzzy logic based on particle swarm optimization algorithm. The main goal of this research is to survey the convergence capability of the particle swarm optimization algorithm using fuzzy logic in intelligent intrusion detection of a designable system. In order to simulate intelligent attacks on a system, KDD99 data are used. Based on the findings, the Particle Swarm Optimization (PSO) algorithm is highly capable of detecting an intelligent attack on a system. In this study, we considered 1800 times attack, in which the PSO algorithm was capable of repelling attacks in 7.24 s and converged. The best convergence occurred at stage 775, and then all attacks were eliminated from the system. Results showed that the stability and convergence of the system improved after each attack. Also, the number of attacks increased to 2500 times to investigate unpredictable intrusions and converge accrued at the attack 771st. Finally, the results obtained by the PSO algorithms were compared to the results obtained by the Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm. The findings indicate that the PSO algorithm is highly capable of detecting intelligent intrusions into a system. It is also suggested to employ this algorithm in cloud computing systems because of its high capability of repelling smart attacks.
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