Automatic Planners for Solid Waste Management in Latin American Smart Cities
摘要
Urban solid waste managementWaste management poses a growing challenge for Latin AmericanLatin America cities due to accelerated urbanization, outdated infrastructure, fragmented governance, and limited technological integration. Despite the global push toward Smart CitiesSmart Cities, many municipalities in the region still rely on manual and reactive waste collection systems, leading to inefficiencies, high operational costs, and environmental risks. In this context, automatic planningAutomatic planning technologies have emerged as promising tools to optimize routing, resource allocation, and real-time decision-making. This study presents a state-of-the-art analysis of automatic planners applied to solid waste disposal management, with particular attention to their adaptability to Latin American urban conditions. Six representative planning systems were reviewed: DecStar, MSP, Complementary1, Complementary2, MAplan1, and MAplan2. The analysis focused on their methodological foundations, heuristic strategies, and applicability to key challenges such as fleet coordination, real-time route optimizationRoute optimization, cost reduction, and predictive planning. A comparative framework was developed to evaluate each planner based on its heuristic logic, advantages, limitations, and suitability for specific operational goals. The study also discusses the technological and data infrastructure requirements needed to implement these systems effectively in the region, including IoT-based data collection, integration of heterogeneous data sources, and context-aware modeling. Results indicate that while each planner offers distinct strengths, their effectivenessEffectiveness depends on robust data environments and tailored integration into local waste systems. In conclusion, automatic planners represent a strategic opportunity to modernize waste managementWaste management in Latin AmericaLatin America, but their success requires a gradual implementation path that begins with data consolidation and is supported by institutional coordination and policy alignment.