Risk, uncertainty, and complexity in building envelope retrofit modeling: energy performance and decision-support methods

Optimization-Based and Optimization-Linked Decision Methods for Building Construction Safety: A Systematic Review

Building construction sites are dynamic systems in which safety decisions interact with time, cost, productivity, equipment movement, and spatial constraints. This systematic review examines how building-construction-stage safety is represented in optimization-based and optimization-linked decision studies published be...

Assessing the expected impact of logistics risks on supply chain performance

This study develops an integrated framework that predicts logistics risks and quantifies their expected impact on supply chain performance. Existing research largely focuses on estimating risk occurrence but rarely evaluates both the likelihood and the potential consequences of disruptions. To address this gap, the...

Decision-making, optimisation, and risk-based asset management: a case study in Dominica

Small Island Developing States (SIDS) face unique challenges, including limited resources and disproportionately high exposure to natural hazards, which complicate the management of their critical road networks. While various risk-based asset management frameworks have been proposed, they are often conceptual and lack...

Integrated Time–Cost–Risk Management in Industrial Construction: A Systematic Review and Unified Analytical Taxonomy

Industrial construction projects involve complex interactions among uncertainty, risk, schedule, and cost, motivating the development of advanced analytical and decision-support methodologies. This study systematically reviews methodological approaches to risk assessment and performance management in industrial constru...

A Risk-Based Decision Framework for Selecting Owner Estimate Percentiles in EPC Projects Using Monte Carlo Simulation and PROMETHEE II

Owner Estimate (OE) determination in Engineering, Procurement, and Construction (EPC) projects remains a challenging process due to high levels of uncertainty arising from technical complexity, market fluctuations, incomplete information, and project-specific risks. Although Monte Carlo Simulation (MCS) can generate pr...

Dynamic Risk