Hierarchical tri-level optimization model for effective use of by-products in a sugarcane supply chain network

Abstract

Developing a solution algorithm for tri-level facility location–allocation problem is always challenging due to the inherent complexity of these problems. The proposed sugarcane supply chain network is a tri-level modeling approach formulated based on the static Stackelberg game between producer, distribution center, sugarcane industry, compost unit, biorefinery unit and market in the framework. The network emphasizes the use of massive amount of the by-products generated in the sugarcane industry. These by-products are excellent raw materials for compost unit and biorefinery units. In such cases decisions are made in the hierarchy. By reviewing the proposed algorithms in the past, it has been realized that the shortcomings of the algorithm could be improved by introducing some efficient search mechanism in the algorithms. In this context, a strong local search mechanism based on social engineering optimizer is developed to intensify search space more carefully. Two-hybrid algorithms, GASEO based on Genetic algorithm and social engineering optimizer, and KASEO based on Keshtel algorithm and social engineering optimizer is proposed. To appraise the performance of the proposed algorithm, we pervasively discussed the parameter tuning using Taguchi approach. The ANOVA and Tukey post-hoc test ensures that the performance of the proposed GASEO is appreciable over other algorithms.