Optimization techniques for green supply chain practice challenges: a systematic hybrid approach

Abstract

Optimization techniques necessitate a diverse focus to overcome green supply chain practice (GSCP) challenges, to address a variety of conflicting problems and uncertain challenges. This study aims to review the literature on optimization techniques for GSCP challenges, revealing the intricate interrelationship among attributes under uncertainty for hierarchical structure construction, and presenting insights and priorities for future research. Data were collected from the Scopus database, resulting in a total of 465 publications. An integrated method of systematic review was used to review and validate the GSCP optimization techniques. Hence, assessments of multi-objective optimization and uncertainty are pivotal for enhancing GSCP. The challenges posed by GSCP underscore the need to use heuristic algorithms, mixed integer programming, goal programming, stochastic programming and the non-dominated sorting genetic algorithm II in practical applications. This study offers a contribution to the literature on GSCP and provides valuable information to assist researchers and practitioners using optimization techniques.