An Application of Goal Programming Variants to Evaluate Outsourcing Strategies in the Clothing Industry

International outsourcing has provided the immense cost savings to the clothing companies. Today, the companies are reconsidering the reshoring and relocation due to the factors such as increasing cost, lead time uncertainty, and demand nature. In such situations, the domestic destinations provide capacity flexibility. Choice of the compatible strategy for a given situation prevents the associated loss in the business. This paper evaluates the outsourcing and reshoring phenomenon based on realistic outsourcing objectives in the textile supply chain. This paper develops a goal programming model to analyze the outsourcing strategies for cost and capacity flexibility. Minimization of the capacity inflexibility was considered as the capacity flexibility. Cost and capacity inflexibility were used as two objective functions. The optimization model was solved using the three important variants of goal programming. Comparison of results from three different techniques provides several insights for precise outsourcing decision making. For instance, the companies can choose a compatible strategy to maintain the cost and capacity flexibility at an acceptable level. Instead of only the cost saving, the reshoring decision making should be based on all the real criteria. The key focus of this paper is the clothing industry. The results may be different for other manufacturing sectors. Due to the increased globalization, the textile companies have been facing various challenges such as outsourcing destination selection for maximum profit and the reshoring debates. To address such challenges, this study provides various insights to the textile industry based on realistic objectives of outsourcing (i.e., cost and capacity flexibility). It is difficult to quantify the flexibility. This paper develops new ideas to quantify the capacity flexibility. The application of three different variants of goal programming provides the alternative solutions.