Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...
Traditional global search heuristics to solve constraint satisfaction problems focus on properties of an individual variable that mandate early search attention. If, however, one ...
The approximate searching problem on compressed text tries to find all the matches of a pattern in a compressed text, without decompressing it and considering that the match of th...
We present a new algorithm that reduces the space complexity of heuristic search. It is most effective for problem spaces that grow polynomially with problem size, but contain lar...
— Job-shop scheduling is one of the most difficult production scheduling problems in industry. This paper proposes an adaptive neural network and local search hybrid approach fo...