Combinatorial Optimization Algorithms for Problem Solving Systems

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In various real situations, it is often required to achieve optimization. The objective of this study is to develop powerful and general-purpose combinatorial optimization algorithms as problem-solving tools. In this study, based on previous works, we considered some techniques for improving the performance of algorithms, and proposed extended models that can handle a wider range of problems. In order to demonstrate the usefulness of our algorithms, we conducted computational experiments for timetabling, nurse scheduling, resource-constrained scheduling and other problems.