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Sourcing decisions with order allocation under supply disruption risk considering quantitative and qualitative criteria

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Abstract

This paper addresses sourcing decisions with order allocation in the presence of supplier disruption risks in a two-echelon supply chain considering both quantitative and qualitative aspects. A mixed-integer linear program is proposed for the optimal supplier selection and order allocation considering finite and expandable production capacity, failure probability, all-unit price discount, and spot-market cost. Due to the time complexity of the problem to get an optimal solution, we develop a heuristic which is found highly efficient in time complexity and highly competitive in solution quality. A multi-objective model is formulated to capture the qualitative aspect of suppliers by maximizing the total purchase value along with minimizing the expected total cost. We have applied NSGA-II and MOPSO, two widely used evolutionary algorithms, to solve the multi-objective model. A numerical illustration is presented along with sensitivity analysis considering a supplier base of twenty suppliers and a sourcing strategy up to six suppliers. It has been found that dual-sourcing and triple-sourcing are mainly part of the non-dominated Pareto front. Also, increasing demand would lead to a higher level of sourcing strategy, which also depends on the maximum capacity of suppliers and the minimum order to be allocated to the selected suppliers.

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Authors and Affiliations

  1. Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721 302, India

    Maheswar Singh Mahapatra, Pravash Chandra Pradhan & J. K. Jha

  2. School of Business, FLAME University, Pune, 412115, India

    Maheswar Singh Mahapatra

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  1. Maheswar Singh Mahapatra
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  2. Pravash Chandra Pradhan
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  3. J. K. Jha
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Correspondence to J. K. Jha.

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Mahapatra, M.S., Pradhan, P.C. & Jha, J.K. Sourcing decisions with order allocation under supply disruption risk considering quantitative and qualitative criteria. Oper Res Int J 22, 3291–3333 (2022). https://doi.org/10.1007/s12351-021-00661-2

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