Sustainable Supply Chain (SSC) management aims at integrating economic, environmental and social goals to assist in the long-term planning of a company and its supply chains. There is no consensus in the literature as to whether social and environmental responsibilities are profit-compatible. However, the conflicting nature of these goals is explicit when considering specific assessment measures and, in this scenario, multi-objective optimization is a way to represent problems that simultaneously optimize the goals. This paper proposes a Lagrangian matheuristic method, called $AugMathLagr$, to solve a hard and relevant multi-objective problem found in the literature. $AugMathLagr$ was extensively tested using artificial instances defined by a generator presented in this paper. The results show a competitive performance of $AugMathLagr$ when compared with an exact multi-objective method limited by time and a matheuristic recently proposed in the literature and adapted here to address the studied problem. In addition, computational results on a case study are presented and analyzed, and demonstrate the outstanding performance of $AugMathLagr$.
An Environmentally Sustainable Closed-Loop Supply Chain Network Design under Uncertainty: Application of Optimization
Rajshahi University of Engineering & Technology (RUET)（拉杰沙希工程技术大学）；University of Arkansas at Little Rock（阿肯色大学小石城分校）；North Dakota State University（北达科他州立大学）；University of Alberta（阿尔伯塔大学）
An Analytical Framework for the Linear Best-Worst Method and its Application to Achieve Sustainable Development Goals--Oriented Agri-Food Supply Chains
A Heuristic Framework of Variable Neighborhood Descent Methods for the Large-Scale Multi-Level Facility Location Problem in Supply Chain Networks
A. R. Sanchez, Jr. School of Business, Texas A&M International University（德克萨斯农工大学国际学院A.R.桑切斯商学院）；School of Business Administration, The University of Mississippi（密西西比大学工商管理学院）
Dynamic Pricing in Smart Grids under Thresholding Policies: Algorithms and Heuristics
Masdar Institute of Science and Technology（马斯达尔理工学院）；Brigham Young University（杨百翰大学）；New York University, Abu Dhabi（纽约大学阿布扎比分校）；Massachusetts Institute of Technology（麻省理工学院）
