An OGSM-based multi-objective optimization model for partner selection in fresh produce supply chain considering carbon emissions

Incorporating partner selection with environmental commitment is recognized as a crucial aspect of green development in fresh produce supply chains. This paper presents a multi-objective programming (MOP) model for partner selection considering carbon emissions based on the ‘Objectives, Goals, Strategies, Measures’ (OGSM) framework. The OGSM serves as a strategic scheme to identify the long-term green development vision of a supply chain, ensuring that the activities of supply chain partners are aligned with common goals. Driven by the OGSM design, the MOP model is formulated with three conflicting objective functions to maximize profit, minimize carbon emission, and maximize the quality of fresh produce. The model helps decision-makers address decisions on partner selection with determined logistics volumes, transportation modes and packaging types under carbon emission constraints. To tackle the NP-hard problem, we develop an effective hybrid meta-heuristic algorithm called ɛ-NSGA, which complements the advantages of the ɛ-constraint method and NSGA-II (Non-dominated Sorting Genetic Algorithm-II). The experimental results based on parameter calibration of the Taguchi method and the Kruskal–Wallis test demonstrate that the proposed ɛ-NSGA outperforms other four heuristic algorithms in terms of the performance indices of GD (Generational Distance), spacing, IGD (Inverted Generational Distance), and HV (Hyper Volume). The implementation of the OGSM-MOP together with ɛ-NSGA in a real-world apple supply chain illustrates the effectiveness and practicality of the model. Finally, managerial insights into the utilization of the model are discussed and suggestions for decision-making to fulfill corporate environmental obligations are provided.