The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this.

This book aims to demonstrate and detail the pervasive nature of Discrete Optimization. While the subject's applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this. The book couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It is done with an academic treatment outlining the state-of-the-art for researchers across the domains of the Computer Science, Math Programming, Applied Mathematics, Engineering, and Operations Research. The book utilizes the tools of mathematical modeling, optimization, and integer programming to solve a broad range of modern problems. The editors are internationally-known research scholars in the field and they have attracted some of the best names in the field to do commissioned chapters in the handbook.

Methods.- The Formulation and Solution of Discrete Optimisation Models.- Continuous Approaches for Solving Discrete Optimization Problems.- Logic-Based Modeling.- Modelling for Feasibility - the Case of Mutually Orthogonal Latin Squares Problem.- Network Modelling.- Modeling and Optimization of Vehicle Routing and Arc Routing Problems.- Applications.- Radio Resource Management.- Strategic and Tactical Planning Models for Supply Chain: An Application of Stochastic Mixed Integer Programming.- Logic Inference and a Decomposition Algorithm for the Resource-Constrained Scheduling of Testing Tasks in the Development of New Pharmaceutical and Agrochemical Products.- A Mixed-Integer Nonlinear Programming Approach to the Optimal Planning of Offshore Oilfield Infrastructures.- Radiation Treatment Planning: Mixed Integer Programming Formulations and Approaches.- Multiple Hypothesis Correlation in Track-to-Track Fusion Management.- Computational Molecular Biology.