A Multi-Objective Possibilistic Programming Model for Relief Logistics Problem

Disaster relief logistics is one of the major activities in disaster management. The significance of accounting for uncertainty in such context stimulates an interest to develop appropriate decision making tools to cope with uncertain and imprecise parameters in relief logistics system design problems. This paper proposes a multi-objective possibilistic non-linear programming model (MOPNLP) to deal with such issues. Our multi-objective model contains: (i) the minimization of the sum of setup cost, transportation costs and shortage costs of commodity in affected area; (ii) the maximization customer satisfaction. The model includes the imprecise nature of some critical parameters such as demands for various types of relief commodities, cost coefficients and capacity levels. To solve the proposed model, a two-phase interactive fuzzy solution approach is developed. Numerical experiments demonstrate the significance and applicability of the developed possibilistic model as well as the usefulness of the proposed solution approach for actual decision making problem.