Optimization Approaches for Dangerous Goods Logistics

Problems and Trade-offs

Abstract

Logistics systems handling dangerous goods operate under stringent regulatory constraints and elevated safety requirements, which fundamentally reshape classical optimization problems. This paper provides a structured overview of the core optimization tasks in dangerous goods logistics, with particular emphasis on transportation, storage, inventory management, facility planning, and fleet allocation. The study highlights how risk exposure, regulatory compliance, and safety considerations are explicitly embedded into optimization models, transforming traditional cost-driven approaches into multi-objective and risk-aware decision frameworks. Through selected numerical examples, the paper illustrates typical trade-offs between logistics cost efficiency and safety performance, such as routing efficiency versus societal risk, inventory buffering versus hazard concentration, and fleet utilization versus system resilience. By synthesizing fragmented research streams and linking theoretical models with illustrative applications, the paper contributes to a more integrated understanding of optimization challenges in dangerous goods logistics and supports decision-makers in balancing efficiency, safety, and regulatory compliance.