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, 2012

"... A reduced integer programming model for the ferry scheduling problem ..."

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### Predictive Control of Timed Hybrid Petri Nets

"... Abstract Hybrid Petri nets represent a powerful modeling formalism that offers the possibility of integrating in a natural way continuous and discrete dynamics in a single net model. Usual control approaches for hybrid nets can be divided into discrete-time and continuous-time approaches. Continuou ..."

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Abstract Hybrid Petri nets represent a powerful modeling formalism that offers the possibility of integrating in a natural way continuous and discrete dynamics in a single net model. Usual control approaches for hybrid nets can be divided into discrete-time and continuous-time approaches. Continuous-time approaches are usually more precise but can be computationally prohibitive. Discrete-time approaches are less complex but can entail mode-mismatch errors due to fixed time discretization. This work proposes an optimization-based event-driven control approach that applies on continuous time models and where the control actions change when discrete events occur. Such an approach is computationally feasible for systems of interest in practice and avoids mode-mismatch errors. In order to handle modelling errors and exogenous disturbances, the proposed approach is implemented in a closed-loop strategy based on event-driven model predictive control.

### Comparisons of Commercial MIP Solvers and an Adaptive Memory (Tabu Search) Procedure for a Class of 0–1 Integer Programming Problems

"... The Boolean optimization problem (BOOP) is a highly useful formulation that embraces a variety of 0-1 integer programming problems, including weighted versions of covering, partitioning and maximum satisfiability problems. In 2006 an adaptive memory (tabu search) method for BOOP was introduced, and ..."

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The Boolean optimization problem (BOOP) is a highly useful formulation that embraces a variety of 0-1 integer programming problems, including weighted versions of covering, partitioning and maximum satisfiability problems. In 2006 an adaptive memory (tabu search) method for BOOP was introduced, and was proved to be effective compared to competing approaches. However, in the intervening years, major advances have taken place in exact solvers for integer programming problems, leading to widely publicized successes by the leading commercial solvers XPRESS, CPLEX and GUROBI. The implicit message is that an alternative methodology for any broad class of IP problems such as BOOPs would now be dominated by the newer versions of these leading solvers. We test this hypothesis by performing new computational experiments comparing the tabu search method for the BOOP class against XPRESS, CPLEX and GUROBI, and documenting improvements provided by the exact codes. The outcomes are somewhat surprising.