{'fraction_non_alphanumeric': 0.018633540372670808, 'fraction_numerical': 0.0, 'mean_word_length': 5.3618421052631575, '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}}
Decision support for supply chain planning under uncertainty

In order to support decision making, this article investigates the planning process of a production unit within a supply chain. The aim is to satisfy the customer demand while respecting the internal constraints of the production unit and those of its supply chain partners. In that purpose, we suggest a mixed-integer linear programming model which is embedded in a dynamic procedure simulating a rolling horizon planning process. A special attention is given to the temporal features of the production unit and of its suppliers (cycle times, anticipation delays) as well as those of the planning process itself (planning horizon, frozen horizons, planning periodicity). Moreover, the proposed framework takes into account flexible demands and to evaluate different planning strategies to face with these flexible demands. Finally, a numerical example highlighting the interest of our approach is given.