Inverse Optimization Method for Safety Resource Allocation and Inferring Cost Coefficient Based on a Benchmark

Due to cost-push inflation, the trade-off between safety costs and risk prevention (safety) has become difficult worldwide. Most companies experience difficulty of cost overruns allocate resource inefficiently. In this paper, a forward model maximizing input is formulated. Because there wide range variation coefficient parameters, it hard determine coefficients in model, make decisions on which types resources are allocated potentially risky locations with what prices, ensure total as close benchmark possible. Taking allocation, themes, resources, parameters new decision variables, inverse optimization formulated based bi-level model. With consideration quaternion decision, programming, NP-hard problem, comparison exact penalty algorithm an improved PSO algorithm, inertia weight adaptively changing number iterations, suitable for solving specific Numerical experiments demonstrated effectiveness proving that can right amount prices at places.