{'fraction_non_alphanumeric': 0.017959183673469388, 'fraction_numerical': 0.0, 'mean_word_length': 5.4526315789473685, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Bi-objective Multistage Decentralized Supply Chain Planning

In this paper, we have considered a multistage decentralized supply chain (SC) with different independent entities where each stage’s decision is made based on more than one objective. To do so, mathematical models are developed based on the concepts of the bilevel planning. Here, a strategy of total SC coordination is proposed as an upper level optimization problem with two objectives which are assumed to be implemented by an independent body. Different multiple objectives are considered in each SC stage as lower level problems. We developed a solution approach and solved the model with a multi-objective genetic algorithm approach using Matlab. From the pareto graph analysis, we considered different scenarios to obtain values that allow the decision-maker to select a suitable solution. Moreover, our proposed model is compared with a single-level centralized approach, with two commonly used objectives from literature. The comparison shows that modelling a complete decentralized SC network with independent entities having individual multiple objectives with our proposed model is more realistic and effective than single-level centralized modelling.