Routing and collection load decisions in a green logistics system for delivering lunch boxes

Purpose: The purpose of this paper is to offer improvement in routing and collection load decisions for a green logistics system that delivers lunch boxes. Design/methodology/approach: A mathematical model is introduced into the literature for the 130 years old logistics systems whose delivery accuracy is better than the Six Sigma standard without using sophisticated tools. A simulated annealing (SA) approach is then used to find the routing and collection load decisions for the lunch box career. Findings: The findings establish that we can improve the world-class lunch box delivery (LBD) system. The suggested improvement in terms of reduction in distance travel is nearly 6%. This could be a huge relief for thousands of lunch box careers. The uniformity in collection load decisions suggested by the proposed approach can be more effective for the elderly lunch box carriers. Research limitations/implications: The research provides a mathematical framework to study an important logistics system that is running with a supreme level of service accuracy. Collecting primary data was challenging as there is no scope for recording and maintaining data in the present logistics system. The replicability of the system for some other city in the world is a challenging question to answer. Practical implications: Better routing and collection load decisions can help many lunch box careers save time and bring homogeneity in workload into the system. Social implications: An efficient routing decision can help provide smoother traffic movements, and uniformity in collection load can help avoid unwanted injuries to about 5,000 lunch box careers. Originality/value: The originality of this paper lies in the proposed mathematical model and finding the routing and collection load decisions using a nature-inspired probabilistic search technique. The LBD system of Mumbai was never studied mathematically. The study is the first of its kind.