A multi-objective robust possibilistic programming approach to coordinating procurement operations in the disaster supply chain using a multi-attribute reverse auction mechanism

Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.

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A fuzzy goal programming approach to solve multi-objective supply chain network design problems

International Journal of Industrial Engineering Computations ◽

10.5267/j.ijiec.2013.04.004 ◽

2013 ◽

Vol 4 (3) ◽

pp. 315-324 ◽

Cited By ~ 4

Author(s):

Amir Abbas Kanani Nezhad ◽

Emad Roghanian ◽

Zahra Azadi

Keyword(s):

Supply Chain ◽

Network Design ◽

Goal Programming ◽

Fuzzy Goal Programming ◽

Programming Approach ◽

Supply Chain Network Design ◽

Supply Chain Network ◽

Design Problems ◽

Multi Objective ◽

Fuzzy Goal

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A Fuzzy Goal Programming Approach for Solving Multi-Objective Supply Chain Network Problems with Pareto-Distributed Random Variables

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488519500259 ◽

2019 ◽

Vol 27 (04) ◽

pp. 559-593 ◽

Cited By ~ 1

Author(s):

Vincent Charles ◽

Srikant Gupta ◽

Irfan Ali

Keyword(s):

Supply Chain ◽

Goal Programming ◽

Fuzzy Goal Programming ◽

Programming Approach ◽

Supply Chain Network ◽

Delivery Time ◽

Demand And Supply ◽

Multi Objective ◽

Weighted Goal Programming ◽

Fuzzy Goal

Uncertainty is unavoidable and addressing the same is inevitable. That everything is available at our doorstep is due to a well-managed modern global supply chain, which takes place despite its efficiency and effectiveness being threatened by various sources of uncertainty originating from the demand side, supply side, manufacturing process, and planning and control systems. This paper addresses the demand- and supply-rooted uncertainty. In order to cope with uncertainty within the constrained multi-objective supply chain network, this paper develops a fuzzy goal programming methodology, with solution procedures. The probabilistic fuzzy goal multi-objective supply chain network (PFG-MOSCN) problem is thus formulated and then solved by three different approaches, namely, simple additive goal programming approach, weighted goal programming approach, and pre-emptive goal programming approach, to obtain the optimal solution. The proposed work links fuzziness in transportation cost and delivery time with randomness in demand and supply parameters. The results may prove to be important for operational managers in manufacturing units, interested in optimizing transportation costs and delivery time, and implicitly, in optimizing profits. A numerical example is provided to illustrate the proposed model.

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