This paper presents a linear fractional programming approach for solving multi objective linear programming problem. We develop a model to solve multi objective linear programming problem into fractional programming problem and proposed a method for linearization of a fractional objective. In particular, we consider the optimization of ratio of profit and cash expenditure as fractional objectiv...

Abstract This paper proposes a multi-objective mixed-integer linear programming to model cold chain with complementary operations on hierarchical hub network. Central hubs are linked each other in the first level of network and star lower-level hubs. As for case study, different levels provide various refreshing or freezing keep perishable goods fresh along Disruption is formulated by considera...

This paper considers a stochastic dynamic inventory problem involving a single item, linear cost structures, and finite distributions (but not necessarily independent) for the stochastic cost and demand parameters. We develop primal and dual algorithms for a multi-stage stochastic linear programming formulation for the problem. The complexity of the proposed algorithms is shown to be within O(N...

This paper considers a stochastic dynamic inventory problem involving a single item, linear cost structures, and finite distributions (but not necessarily independent) for the stochastic cost and demand parameters. We develop primal and dual algorithms for a multi-stage stochastic linear programming formulation for the problem. The complexity of the proposed algorithms is shown to be within O(N...

Abstract In studying petroleum supply chain networks, past studies have largely segregated three critical decision-making aspects: integrated planning, uncertainties, and multi-objective setting. This study focuses on consolidating these aspects proposes a stochastic, multi-objective, mixed-integer linear programming model for strategic tactical planning of downstream (DPSC) networks. Demand, c...

Traditional Data Envelopment Analysis (DEA) models evaluate the efficiency of decision making units (DMUs) with common crisp input and output data. However, the data in real applications are often imprecise or ambiguous. This paper transforms fuzzy fractional DEA model constructed using fuzzy arithmetic, into the conventional crisp model. This transformation is performed considering the goal pr...