The explosive growth of e-commerce has transformed how goods move through our cities. In metropolitan areas like Jakarta, millions of parcels flow daily from online merchants to consumers, creating unprecedented logistics challenges. Platform-based logistics service providers, companies that connect suppliers to customers through digital applications, must coordinate this complex system of pickups and deliveries while meeting increasingly demanding consumer expectations for same- and next-day delivery. This dissertation addresses a fundamental gap between modern metropolitan logistics and traditional optimization methods. Classical approaches in Operations Research were developed for stable, predictable environments with complete information. However, metropolitan logistics operates in a fundamentally different reality: orders arrive continuously throughout the day, traffic conditions fluctuate hourly, and decisions cascade across multiple operational levels. A routing choice in one city potentially affects consolidation options across the entire metropolitan network, while a delay in a morning pickup can disrupt afternoon deliveries in another city entirely. Through collaboration with an Indonesian logistics service provider operating primarily in the Jakarta Metropolitan Area, this research identifies and addresses eight critical challenges that define metropolitan logistics complexity. These span structural challenges (how to consolidate orders and coordinate different vehicle types across multi-layered networks), operational challenges (managing simultaneous pickups and deliveries under strict time commitments), and dynamic environment challenges (responding to unpredictable order arrivals and time-varying traffic conditions). To address these interconnected challenges, this dissertation contains three complementary studies. The first establishes a model for coordinating two-echelon distribution within single cities, where parcels move between customers and central hubs via satellite facilities, with vehicles performing both pickups and deliveries while respecting specific deadlines. The second develops an operational framework for multiple interconnected cities, enabling real-time decisions about order-to-inter-city transport allocation and vehicle dispatch timing when orders arrive stochastically. The third proposes a methodology that incorporates time-dependent travel times reflecting actual traffic patterns, enabling more realistic routing decisions in congested urban environments. The solutions combine mathematical modeling with pragmatic algorithmic design to strike a balance between solution quality and computational efficiency. These include combining metaheuristic search with exact optimization, utilizing cost function approximation for decision-making under uncertainty, and employing dynamic network construction techniques that adapt to the problem’s complexity. Real-world implementation demonstrates substantial impact. In Jakarta, integrating previously separated pickup and delivery operations can reduce routing costs by up to 17.5%. Strategic order assignment considering both immediate costs and future routing flexibility achieved 30.5% cost reductions compared to current practices. These improvements stem from three key insights: operational coupling (combining previously separate activities), integrated optimization (coordinating decisions across the logistics network), and practical simplicity (using straightforward yet effective methods that can be implemented in real-world systems). This research advances the state-of-the-art by introducing new problem formulations that capture metropolitan logistics complexity, developing solution methods that scale to real-world operations, and providing validated frameworks that bridge the gap between academic optimization and industrial practice. For logistics companies operating in dense urban environments worldwide, these findings offer actionable strategies for improving efficiency while maintaining service quality. As e-commerce continues its rapid expansion and cities grow ever denser, the models and methods developed here provide essential tools for managing the increasingly complex flow of goods through our metropolitan areas.