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| Preface | ||
| 1 | Constraint Satisfaction Methods | 1 |
| 2 | Extending a General-Purpose Algebraic Modeling Language to Combinatorial Optimization: A Logic Programming Approach | 31 |
| 3 | Disjunctive Programming and Cooperating Solvers | 75 |
| 4 | An Annotated Bibliography for Post-solution Analysis in Mixed Integer Programming and Combinatorial Optimization | 97 |
| 5 | Stochastic Knapsack Problem | 149 |
| 6 | Sample-Path Solutions for Simulation Optimization Problems and Stochastic Variational Inequalities | 169 |
| 7 | Play Selection in American Football: a Case Study in Neuro-Dynamic Programming | 189 |
| 8 | Tabu Search Candidate List Strategies in Scheduling | 215 |
| 9 | GA's and Surrogate Constraints for MCKPs | 235 |
| 10 | Introduction to Genetic Heuristics and Vehicle Routing Problems with Complex Constraints | 253 |
| 11 | A Genetic Algorithm for the Clustered Traveling Salesman Problem with a Prespecified Order on the Clusters | 287 |
| 12 | A New Algorithm for the Site-Dependent Vehicle Routing Problem | 301 |
| Price | Condition | Delivery | Seller | Action |
| $209.00 | Digital |
| WonderClub |
David Corsi
reviewed Advances in Computational and Stochastic Optimization, Logic Programming, and Heuristic Search on March 31, 2017
Advances in Computational and Stochastic Optimization, Logic Programming, and Heuristic Search
In comparison to "Introduction to Algorithms" (the other algorithm book I had significant exposure to) this one is faster to read, easier to digest and more tailored towards applications.
I found the "Hitchhiker's Guide to Algorithms" in the back to be extremely useful if you really find yourself tackling an algorithmic problem in practice.
The main part (maybe skipping/skimming down a few chapters) is a very good preparation for algorithm-heavy job interviews (e.g. Google, Facebook etc ...).
Very much recommended.
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