Prospects and challenges of ripple spreading algorithm for waste collection path optimization problem in Indonesia

Abstract

Nowadays, countering the complexity of waste collection path optimization problems (POP) are reliably solved through evolutionary computation (EC). However, a sustainable collection strategy requires a specific rule and outcome for a given route network. Most waste managers are concerned with expenditure, work hours, and ecological footprints, combined with model flexibility to mimic real-life execution for the specific study case. Contemporary stochastic and deterministic POP methods are every so often confronted with optimality and scalability. Beyond its predecessor, namely the A∗ and the Dijkstra algorithm, a fundamental nature-based deterministic algorithm called a Ripple-Spreading Algorithm (RSA) had performed a straightforward heuristic evaluation. This study investigates prospects and future challenges in developing the RSA simulation based on Indonesia's waste management scope. Specific overseas theme literature was employed to explore the possible research setting.