The need for solutions to combinatorial optimization problems such as scheduling, manufacturing, and network optimization arises both in theoretical research and industrial applications. General-purpose solvers are keys to those solutions as tools that researchers and practitioners first try to use. In combinatorial optimization, satisfiability (SAT) solvers for propositional logical formulas and integer programming (IP) solvers that search for an optimal solution satisfying constraints have been developed for many years, and non-experts of algorithms can even solve several real-scale problems. Namely, the cutting-edge technology of algorithms is used in societies through those general-purpose solvers by people without noticing them.

The development of general-purpose solvers is not merely a coding technique of algorithms, but an important academic research topic as “implementation technology.” For example, the research of SAT solvers started as automatic theorem proving in the 1960s and has been publishing research papers in premier conferences related to artificial intelligence (AI) since 2000 as an important research topic.

A general-purpose implementation technology for combinatorial reconfiguration is not yet established. On the other hand, a few successful examples can be found, for example, in switching procedures of power distribution networks. Group B01 aims at founding the implementation technology of combinatorial reconfiguration based on those successful examples.