Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...

In a ground-breaking study, six researchers from universities from five countries, including one from the American University ...

Supply chains consist of imperfect humans struggling to make perfect decisions. In the end, though, it all comes down to a ...

Abstract: Under the background of rapid development of global LNG industry, improving the energy efficiency of compressor control system has become the focus of industry attention. This paper proposes ...

Contributions of this work Introduce a multi-objective CMI optimization model which includes the CMI Parameters. Propose an adaptive multi-objective optimization algorithm to solve the assignment ...

The multi-objective optimization program presented can be adapted to other environmental management problems, ... N.-B. (1998) Water pollution control in the river basin by fuzzy genetic ...

Prerna, Vikas Sharma, An Algorithm for Bi-Objective Integer Linear Programming Problem, Filomat, Vol. 36, No. 16 (2022), ... M. Ehrgott and X. Gandibleux, Asurvey and annotated bibliography of ...

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the development of an innovative hybrid algorithm that combines the advantages of classical and quantum computing to ...

The evolutionary algorithm of differential evolution and Pareto optimization model were used for multi-objective optimization to get the reconfiguration of diversified cropping systems with multi ...