Fuzzy Logic Approach for Evaluating Electromobility Alternatives in Last-Mile Delivery: Belgrade as a Case Study DOI Creative Commons
Dragan Lazarević,

D Popović,

Muhammed Yasin Çodur

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(24), P. 6307 - 6307

Published: Dec. 13, 2024

This paper proposes a methodology based on the fuzzy approach, which provides decision-making support to organizer of last-mile delivery (LMD) in selecting sustainable models for specific territory. Solving this task is essential ensure that process efficient and aligned with all three dimensions development. The goal select most suitable electromobility alternative implementation characteristics requirements current circumstances. proposed involves creation mechanism consisting series logic systems will model expert opinions produce preference value as output, defining suitability applying particular LMD model. A methodological contribution harmonized membership functions variables result comparing symmetric asymmetric aimed at achieving valid results. results guide making best decision when choosing from analyzed models. applicability adequacy are demonstrated through analysis case study focused evaluation alternatives part city Belgrade. obtained values, range 0 1 tested variants, follows within interval: [0.481, 0.776] e-motorcycles, [0.376, 0.564] e-cargo bikes, [0.5, 0.624] e-scooters. values these indicators aim decision-makers defined given constraints.

Language: Английский

Prioritization of Preventive Measures: A Multi-Criteria Approach to Risk Mitigation in Road Infrastructure Projects DOI Creative Commons
Aleksandar Senić, Marija Ivanović, Momčilo Đobrodolac

et al.

Mathematics, Journal Year: 2025, Volume and Issue: 13(2), P. 278 - 278

Published: Jan. 16, 2025

Risk management in construction projects is a critical process aimed at identifying, evaluating, and mitigating potential risks that could impact project performance. Preventive measures play central role this process, serving as proactive strategies to minimize the likelihood of on outcomes. This study involved 37 experts from multidisciplinary fields related road infrastructure, ensuring diverse comprehensive perspective risk evaluation prevention. The DELPHI method was employed systematically define key their corresponding preventive measures, providing structured foundation for further analysis. evaluated 302 across 56 using 4 predefined criteria: implementation costs, time required implementation, complexity, probability success. A multi-criteria decision making (MCDM) approach then applied analyze these evaluations, enabling prioritization allocation resources toward most effective strategies. Additionally, fuzzy logic validate results, complementary MCDM methodology. results research provide robust framework management, offering practical guidance makers industry. By integrating expert judgment, systematic evaluation, advanced analytical methods, delivers actionable insights establishes reliable methodology enhancing effectiveness mitigation infrastructure projects.

Language: Английский

Citations

3
Development of a Hybrid Model for Risk Assessment and Management in Complex Road Infrastructure Projects DOI Creative Commons
Aleksandar Senić, Nevena Simić, Momčilo Đobrodolac

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(5), P. 2736 - 2736

Published: March 4, 2025

During the execution of road infrastructure projects, project managers face significant challenges, including financial, technical, regulatory, and operational risks. More than 90% projects have incurred costs exceeding initial estimates, impacting both completion timelines efficiency infrastructure. Effectively assessing managing these risks is crucial for improving outcomes ensuring sustainability investments. To address this study developed a hybrid model risk assessment management in projects. The quantifies across seven key categories: Design, External, Resource, Employer, Contractor, Engineer, Project, based on three primary input factors: Environment coefficient, Contractual Design coefficient. Initially, various machine learning models, linear regression, Random Forest, Gradient Boosting, Stacking Models, neural networks, were applied to assess predictions. However, due specific nature dataset, models did not achieve satisfactory predictive accuracy. As result, fuzzy logic systems (Mamdani Sugeno) employed, demonstrating superior performance modeling occurrence probabilities. Comparative analysis between two approaches revealed that Sugeno provided most accurate findings highlight benefits applying complex providing structured framework enhancing decision-making processes. This provides methodology accurately predicting safety, efficiency, long-term sustainability.

Language: Английский

Citations

1
The Influence of Vehicle Color on Speed Perception in Nighttime Driving Conditions DOI Open Access
Nenad Marković, Aleksandar Trifunović,

Tijana Ivanišević

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3591 - 3591

Published: April 16, 2025

Vehicle color coatings have long been recognized as a factor influencing road safety, particularly regarding their impact on speed perception and crash risk. This study aims to examine how different vehicle affect drivers’ of under nighttime driving conditions, with specific focus sustainability visibility. A controlled laboratory experiment was conducted using simulator replicate realistic night traffic scenarios. total 161 participants evaluated passenger vehicles in four distinct treatments, white (high-reflective paint), yellow (matte safety film), blue (glossy metallic finish), black (low-reflective coating), at two speeds: 30 km/h 50 km/h. Participants’ perceived speeds were collected analyzed standardized statistical methods. Results indicated consistent pattern: overestimated underestimated across all colors. Lighter-colored (white yellow) moving faster than darker-colored (blue black), significant differences between (30 km/h), (50 km/h). Additionally, female tended estimate higher male most conditions. Other individual factors, such place residence, driver’s license type, experience, frequency driving, also showed measurable effects perception. By accounting for diverse demographic characteristics, the highlights perceptual biases related can influence driver behavior. These findings emphasize importance considering strategies, including education, design, policy development aimed reducing

Language: Английский

Citations

0
Artificial intelligence in risk management within the realm of construction projects: A bibliometric analysis and systematic literature review DOI Creative Commons

Kun Tian,

Zicheng Zhu, Jasper Mbachu

et al.

Journal of Innovation & Knowledge, Journal Year: 2025, Volume and Issue: 10(3), P. 100711 - 100711

Published: May 1, 2025

Language: Английский

Citations

0
Fuzzy Logic Approach for Evaluating Electromobility Alternatives in Last-Mile Delivery: Belgrade as a Case Study DOI Creative Commons
Dragan Lazarević,

D Popović,

Muhammed Yasin Çodur

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(24), P. 6307 - 6307

Published: Dec. 13, 2024

This paper proposes a methodology based on the fuzzy approach, which provides decision-making support to organizer of last-mile delivery (LMD) in selecting sustainable models for specific territory. Solving this task is essential ensure that process efficient and aligned with all three dimensions development. The goal select most suitable electromobility alternative implementation characteristics requirements current circumstances. proposed involves creation mechanism consisting series logic systems will model expert opinions produce preference value as output, defining suitability applying particular LMD model. A methodological contribution harmonized membership functions variables result comparing symmetric asymmetric aimed at achieving valid results. results guide making best decision when choosing from analyzed models. applicability adequacy are demonstrated through analysis case study focused evaluation alternatives part city Belgrade. obtained values, range 0 1 tested variants, follows within interval: [0.481, 0.776] e-motorcycles, [0.376, 0.564] e-cargo bikes, [0.5, 0.624] e-scooters. values these indicators aim decision-makers defined given constraints.

Language: Английский

Citations

1