this paper explores the capabilities of multi-objective particle swarm optimization algorithmin a simulation-optimization model for solving waste load allocation problems. the main goals are totaltreatment costs, violation of the water quality standards and equity. in this research, the water qualitysimulation model is coupled with a multi-objective optimization model, mopso. in order to derive...

In this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. Two objective functions, real power loss and energy not supplied index (ENS), were utilized. Multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

Gennaro et al. (Crypto 2010) introduced the notion of verifiable computation, which allows a computationally weak client to outsource the computation of a function F on dynamically chosen inputs x1, . . . , x` to a more powerful but untrusted server. Following a pre-processing phase (that is only carried out once), the client can send some representation of its input xi to the server; the serve...

In this paper, we present an algorithm for learning nondeterministic multi-agent planning domains from execution examples. The algorithm uses a master-slave decomposition of two population-based stochastic local search algorithms and integrates binary decision diagrams to reduce the size of the search space. Our experimental results show that the learner has high convergence rates due to an agg...