Modeling and Optimization of Sustainable Reverse Logistics Enterprise

逆向物流(RL)是从消费者向零售商或制造商收集、检验、分类和处置退回和/或用过的产品的过程。产品回收和处置在逆向物流中的重要性在过去几十年里稳步增长(2016年，仅在美国，RL成本就达到9,020亿美元，见https://www.hollingsworthllc.com/guide-reverse-logistics/).逆向物流被视为可持续发展的重要贡献者，可持续发展可以被定义为“在不损害后代满足自身需求的能力的情况下满足当代人的需求的能力”。制造商收集废旧产品以重复使用或回收利用的主要原因有三个：(I)政府或环境组织实施的产品回收法律，如针对原始设备制造商(OEM)的废旧电器和电子设备(WEEE)指令。根据这一指令，OEM负责收集他们的二手产品并保持环境清洁；(Ii)通过重复使用或回收材料可以产生的利润；以及(Iii)打着环保公司旗号的重要性。这些动机包括一家公司有必要在其个人资料中包括RL活动，以从重复使用或回收旧产品中获得生态、经济和社会效益。只有在做出正确的处置选择和有效地进行产品退货的情况下，制造商才能获得RL的好处。导致实施RL计划的复杂性的因素包括：退回产品的时间、数量和质量的变异性。虽然制造系统已经达到了很高的效率和效果，但RL活动或再制造系统仍然远远落后。这是由于一系列原因，包括：缺乏完善的业绩衡量模型、独特的预测模型和框架，以及采用新的或新兴的技术。这项研究计划旨在通过采用更全面的建模技术和方法来理解和解决RL的复杂性。将使用基于代理的模拟和建模技术、元启发式方法、随机运筹学以及其他技术和技术，如数字孪生。它还倡导再制造商之间以及再制造商和学术界之间更多的合作，以提高RL设计和运营的效率和效果。简而言之，拟议的研究计划旨在支持可持续发展和最大化逆向物流企业的盈利能力。这反过来将提高制造商的社会、“绿色”或“生态”形象。

Reverse logistics (RL) is the process of collection, inspection, sorting and disposition of returned and/or used products from the consumer to a retailer or manufacturer. The importance of product recovery and disposition in reverse logistics is steadily growing since the past few decades (in 2016, in USA alone, RL costs have been $902 billion, see https://www.hollingsworthllc.com/guide-reverse-logistics/). Reverse logistics is seen as a vital contributor to sustainability, which can be defined as the ability to "meet the needs of the present generation without compromising the ability of future generations to meet their own needs." There are three main reasons for a manufacturer to collect used products for reuse or recycle: (i) the product take-back laws imposed by government or environmental organizations, like the waste electrical and electronic equipment (WEEE) directive on the original equipment manufacturers (OEM). Under this directive, OEM take responsibility to collect their used products and keep the environment clean; (ii) the profit that can be generated by reusing or recovering material; and (iii) the importance of falling under the banner of an environmentally conscious company. These motives encompass the necessity for a company to include RL activities in its profile to seize the ecological, economic and social benefits from reusing or recycling a used product. Manufactures may reap benefits of RL only if correct disposition options are made and the return of products is done effectively. The factors that cause complexity in carrying out a RL program include: variability of the time, the quantity, and the quality of returned products. While manufacturing systems have reached a high level of efficiency and effectiveness, RL activities or remanufacturing systems are still far behind. This is due to an array of reasons including: lack of well-established performance measurement models, distinctive forecasting models and frameworks, and adoption of new or emerging technologies. This research program aims at understanding and addressing RL intricacies by employing more comprehensive modeling techniques and approaches. Agent-based simulation and modeling techniques, meta-heuristics methods, stochastic operations research, and other techniques and technologies such as digital twin will be used. It also advocates for more collaboration among remanufacturers and between remanufacturers and academics to improve efficiency and effectiveness of RL design and operation. To recapitulate, the proposed research program aims at supporting sustainability and maximizing reverse logistics enterprise profitability. This in turn shall enhance the social, "green," or "eco" image of the manufacturers.