A Multiobjective Optimization Model for Continuous Allocation of Emergency Rescue Materials

Emergency rescue operations play a vital role in alleviating human suffering, reducing casualties, and cutting down economic losses. One key aspect in the management of these operations is the rational allocation of emergency relief materials, where the allocation is continuous, dynamic, and concurrent. This allocation should be made not only to minimize the emergency rescue losses, but also to reduce the cost of emergency rescue work. A reasonable and effective allocation scheme for emergency relief materials can be established to adapt to the continuity, dynamics, and concurrency of material distribution. In this work, we propose a multiobjective optimization model of emergency material allocation with continuous time-varying supply and demand constraints, where the objective is to minimize the losses and the economic cost incurred by the emergency rescue operations. The constrained optimization problem is handled through sequential unconstrained minimization techniques, and the multiobjective optimization is carried out by the fast nondominated sorting genetic algorithm (NSGA-II) with an elite strategy to obtain a Pareto solution set with fairness and balance of loss and cost. The loss and cost associated with the Pareto frontier are employed to find an appropriate noninferior solution and its corresponding material allocation scheme. We verify through several simulations the model feasibility and the effectiveness of the proposed method, which can provide decision support for continuous material allocation in emergency rescue operations.