Applying fuzzy goal programming to production/transportation planning decisions in a supply chain

In real-world production/transportation planning decision (PTPD) problems in a supply chain, because of the conflicting nature of the multiple objectives and the vagueness in information regarding the environmental coefficients and related parameters, conventional deterministic methods are unsuitable for yielding an effective solution. This study presents a fuzzy goal programming approach for solving the integrated PTPD problems with fuzzy multiple goals in uncertain environments. The proposed model aims to simultaneously minimize the total distribution and production costs, the total number of rejected items, and the total delivery time with reference to available capacity, labor level and quota flexibility constraints at each source, as well as forecasting demand and warehouse space at each destination. The proposed approach adopts the piecewise linear membership functions to represent the fuzzy goals of the decision maker for the integrated PTPD problems in a supply chain, and achieves more flexible doctrines via an interactive decision-making process. The analytical results obtained by implementing an industrial case indicate that the proposed approach is practically applicable for the solving the integrated multi-objective PTPD problems in uncertain environments, and can effectively improve producer/distributor relationships in a supply chain.