Robust Bi-Level Optimization for Maritime Emergency Materials Distribution in Uncertain Decision-Making Environments

Abstract

Maritime emergency materials distribution is a key aspect of maritime emergency responses. To effectively deal with the challenges brought by the uncertainty of the maritime transport environment, the multi-agent joint decision-making location-routing problem of maritime emergency materials distribution (MEMD-LRP) under an uncertain decision-making environment is studied. First, two robust bi-level optimization models of MEMD-LRP are constructed based on the effect of the uncertainty of the ship’s sailing time and demand of emergency materials at the accident point, respectively, on the premise of considering the rescue time window and priority of emergency materials distribution. Secondly, with the help of robust optimization theory and duality theory, the robust optimization models are transformed into robust equivalent models that are easy to solve. Finally, a hybrid algorithm based on the ant colony and tabu search (ACO-TS) algorithm solves multiple sets of numerical cases based on the case design of the Bohai Sea area, and analyzes the influence of uncertain parameters on the decision making of MEMD-LRP. The study of MEMD-LRP under uncertain decision-making environments using bi-level programming and robust optimization methods can help decision makers at different levels of the maritime emergency logistics system formulate emergency material reserve locations and emergency material distribution schemes that can effectively deal with the uncertainty in maritime emergencies.

Research on emergency logistics information traceability model and resource optimization allocation strategies based on consortium blockchain

“…Our objective is to optimize logistics distribution costs, meet demand priorities, reduce transit times, and ensure the accuracy and timeliness of information traceability. To this end, we have constructed a complex multi-objective optimization function (1):…”

“…The C-PBFT consensus mechanism requires that the total number of honest nodes in the network satisfies N � 3f + 1, which means f � NÀ 1 3 . This implies that the model can tolerate up to NÀ 1 3 faulty nodes.…”

“…As globalization accelerates, societal activities are becoming more complex, leading to frequent occurrences of various emergency events. These events underscore the crucial role of emergency logistics in ensuring rapid response and timely resource allocation [1][2][3][4]. However, the current emergency logistics system faces significant challenges, such as information asymmetry, a lack of process transparency, and difficulties in assigning responsibilities, all of which severely impact its efficiency and reliability [5][6][7].…”