A meta-heuristic based approach for solving the single-item lot-sizing problem with a flow shop with energy and environmental constraints

Abdelkader Mechaacha, F. Belkaid
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Abstract

In our work, we proposed at first an extension of a mathematical model of the capacitated single-item lot-sizing problem with a flow shop configuration and multiple energy suppliers, renewable and non-renewable ones. We used an eco-friendly constraint to push the manufacturer toward getting its electricity from renewable energy suppliers. Even if it's not cost-effective to do so, renewable energy has a much lower carbon footprint. The obtained model was implemented in solver software and simulated annealing meta-heuristic algorithm to compare the two solution approaches. For small-sized instances both approaches proved to be effective in terms of solution quality and compilation time, meanwhile, for large-sized instances, the solver couldn't find the optimal solution within a one-hour compilation time. For the meta-heuristic, it gave satisfactory results, especially in terms of the time needed for compilation.
一种基于元启发式的求解具有能源和环境约束的流水车间单品批量问题的方法
在我们的工作中,我们首先提出了一个有能力的单项目批量问题的数学模型的扩展,该模型具有流车间配置和多个能源供应商,可再生和不可再生的。我们使用了一个环保的约束来推动制造商从可再生能源供应商那里获得电力。即使这样做不划算,可再生能源的碳足迹也要低得多。在求解器软件和模拟退火元启发式算法中实现所得到的模型,比较两种求解方法。对于小型实例,两种方法在求解质量和编译时间方面都是有效的,而对于大型实例,求解器在1小时的编译时间内无法找到最优解。对于元启发式,它给出了令人满意的结果,特别是在编译所需的时间方面。
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