Integration of AI and OR techniques in constraint programming for combinatorial optimization problems

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The book explores various advanced topics in computational sustainability and optimization. It begins with a discussion on a MIP-Cut metascheme and addresses challenges in CPAIOR. Key contributions include lazy clause generation that merges SAT, CP, and potentially MIP solving, and insights on matrices, automata, and double counting. The text also delves into the increasing Nvalue constraint and enhancements to the Held and Karp approach via constraint programming. Further, it characterizes and automates matching-based neighborhoods and presents rapid learning techniques for binary programs. Hybrid methods are proposed for sequencing problems in multileaf collimators, while the exploitation of subproblem equivalence in constraint programming is examined. The application of logic-based Benders decomposition for scheduling over long time horizons is discussed alongside integrated maintenance scheduling for semiconductor manufacturing. Additional topics cover service consolidation through constraint programming, wildlife conservation connected subgraph problems, and revisiting the bin packing constraint. The framework for Gomory’s mixed-integer cuts and disjunctive optimization is introduced, alongside a SAT encoding for multi-dimensional packing issues. Job shop scheduling is tackled with setup times, and vehicle routing for food rescue programs is compared across different methodologies. The book also highlights automated co