2021 IEEE Symposium Series on Computational Intelligence (SSCI), Dec 5, 2021
Rank aggregation has many applications in computer science, operations research, and group decisi... more Rank aggregation has many applications in computer science, operations research, and group decision-making. This paper introduces lower bounds on the Kemeny aggregation problem when the input rankings are non-strict (with and without ties). It generalizes some of the existing lower bounds for strict rankings to the case of non-strict rankings, and it proposes shortcuts for reducing the run time of these techniques. More specifically, we use Condorcet criterion variations and the Branch & Cut method to accelerate the lower bounding process.
This paper presents a methodology to solve the long-term transmission network expansion planning ... more This paper presents a methodology to solve the long-term transmission network expansion planning problem considering L-l reliability. The methodology supplements an underlying mixed-integer linear programming formulation with cutting planes derived from structural insights of bus-angle differences involving buses connected by paths of existing and/or expansion lines. The addition of these cutting planes expedites the solution process by yielding tighter relaxation bounds within a branch-and-cut framework, thereby reducing computational times and memory requirements. In order to solve the resulting problems, this work uses the AMPL modeling language interfaced with the CPLEX mathematical programming solver. The practicality of the methodology is tested via the Southern Brazilian System, yielding very promising results.
SIAM Journal on Matrix Analysis and Applications, 2019
The roundoff-error-free (REF) LU factorization, along with the REF forward and backward substitut... more The roundoff-error-free (REF) LU factorization, along with the REF forward and backward substitution algorithms, allows a rational system of linear equations to be solved exactly and efficiently. T...
SIAM Journal on Matrix Analysis and Applications, 2017
The roundoff-error-free (REF) LU and Cholesky factorizations, combined with the REF substitution ... more The roundoff-error-free (REF) LU and Cholesky factorizations, combined with the REF substitution algorithms, allow rational systems of linear equations to be solved exactly and efficiently by worki...
This paper introduces load shed recovery actions for transmission networks by presenting the dc o... more This paper introduces load shed recovery actions for transmission networks by presenting the dc optimal load shed recovery with transmission switching model (DCOLSR-TS). The model seeks to reduce the amount of load shed, which may result due to transmission line and/or generator contingencies, by modifying the bulk power system topology. Since solving DCOLSR-TS is computationally difficult, the current work also develops a heuristic (MIP-H), which improves the system topology while specifying the required sequence of switching operations. Experimental results on a list of N-1 and N-2 critical contingencies of the IEEE 118-bus test case demonstrate the advantages of utilizing MIP-H for both online load shed recovery and recurring contingency-response analysis. This is reinforced by the introduction of a parallelized version of the heuristic (Par-MIP-H), which solves the list of critical contingencies close to 5x faster than MIP-H with 8 cores and up to 14x faster with increased computational resources. The current work also tests MIP-H on a real-life, large-scale network in order to measure the computational performance of this tool on a real-world implementation.
ABSTRACT In many different applications of group decision-making, individual ranking agents or ju... more ABSTRACT In many different applications of group decision-making, individual ranking agents or judges are able to rank only a small subset of all available candidates. However, as we argue in this article, the aggregation of these incomplete ordinal rankings into a group consensus has not been adequately addressed. We propose an axiomatic method to aggregate a set of incomplete rankings into a consensus ranking; the method is a generalization of an existing approach to aggregate complete rankings. More specifically, we introduce a set of natural axioms that must be satisfied by a distance between two incomplete rankings; prove the uniqueness and existence of a distance satisfying such axioms; formulate the aggregation of incomplete rankings as an optimization problem; propose and test a specific algorithm to solve a variation of this problem where the consensus ranking does not contain ties; and show that the consensus ranking obtained by our axiomatic approach is more intuitive than the consensus ranking obtained by other approaches.
2021 IEEE Symposium Series on Computational Intelligence (SSCI), Dec 5, 2021
Rank aggregation has many applications in computer science, operations research, and group decisi... more Rank aggregation has many applications in computer science, operations research, and group decision-making. This paper introduces lower bounds on the Kemeny aggregation problem when the input rankings are non-strict (with and without ties). It generalizes some of the existing lower bounds for strict rankings to the case of non-strict rankings, and it proposes shortcuts for reducing the run time of these techniques. More specifically, we use Condorcet criterion variations and the Branch & Cut method to accelerate the lower bounding process.
This paper presents a methodology to solve the long-term transmission network expansion planning ... more This paper presents a methodology to solve the long-term transmission network expansion planning problem considering L-l reliability. The methodology supplements an underlying mixed-integer linear programming formulation with cutting planes derived from structural insights of bus-angle differences involving buses connected by paths of existing and/or expansion lines. The addition of these cutting planes expedites the solution process by yielding tighter relaxation bounds within a branch-and-cut framework, thereby reducing computational times and memory requirements. In order to solve the resulting problems, this work uses the AMPL modeling language interfaced with the CPLEX mathematical programming solver. The practicality of the methodology is tested via the Southern Brazilian System, yielding very promising results.
SIAM Journal on Matrix Analysis and Applications, 2019
The roundoff-error-free (REF) LU factorization, along with the REF forward and backward substitut... more The roundoff-error-free (REF) LU factorization, along with the REF forward and backward substitution algorithms, allows a rational system of linear equations to be solved exactly and efficiently. T...
SIAM Journal on Matrix Analysis and Applications, 2017
The roundoff-error-free (REF) LU and Cholesky factorizations, combined with the REF substitution ... more The roundoff-error-free (REF) LU and Cholesky factorizations, combined with the REF substitution algorithms, allow rational systems of linear equations to be solved exactly and efficiently by worki...
This paper introduces load shed recovery actions for transmission networks by presenting the dc o... more This paper introduces load shed recovery actions for transmission networks by presenting the dc optimal load shed recovery with transmission switching model (DCOLSR-TS). The model seeks to reduce the amount of load shed, which may result due to transmission line and/or generator contingencies, by modifying the bulk power system topology. Since solving DCOLSR-TS is computationally difficult, the current work also develops a heuristic (MIP-H), which improves the system topology while specifying the required sequence of switching operations. Experimental results on a list of N-1 and N-2 critical contingencies of the IEEE 118-bus test case demonstrate the advantages of utilizing MIP-H for both online load shed recovery and recurring contingency-response analysis. This is reinforced by the introduction of a parallelized version of the heuristic (Par-MIP-H), which solves the list of critical contingencies close to 5x faster than MIP-H with 8 cores and up to 14x faster with increased computational resources. The current work also tests MIP-H on a real-life, large-scale network in order to measure the computational performance of this tool on a real-world implementation.
ABSTRACT In many different applications of group decision-making, individual ranking agents or ju... more ABSTRACT In many different applications of group decision-making, individual ranking agents or judges are able to rank only a small subset of all available candidates. However, as we argue in this article, the aggregation of these incomplete ordinal rankings into a group consensus has not been adequately addressed. We propose an axiomatic method to aggregate a set of incomplete rankings into a consensus ranking; the method is a generalization of an existing approach to aggregate complete rankings. More specifically, we introduce a set of natural axioms that must be satisfied by a distance between two incomplete rankings; prove the uniqueness and existence of a distance satisfying such axioms; formulate the aggregation of incomplete rankings as an optimization problem; propose and test a specific algorithm to solve a variation of this problem where the consensus ranking does not contain ties; and show that the consensus ranking obtained by our axiomatic approach is more intuitive than the consensus ranking obtained by other approaches.
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Papers by Adolfo R Escobedo