A Fast Insertion Tabu Search with Conflict-Avoidance Heuristic for the Multisatellite Multimode Crosslink Scheduling Problem

An agile earth-observing satellite equipped with multimode cameras capable of transmitting observation data to other satellites is developed to rapidly respond to requests with multiple observation modes.This gives rise to the Multisatellite Multimode Crosslink Scheduling(MMCS)problem,which involves allocating observation requests to agile satellites,selecting appropriate timing and observation modes for the requests,and transmitting the data to the ground station via the satellite communication system.Herein,a mixed integer programming model is introduced to include all complex time and operation constraints.To solve the MMCS problem,a two-stage heuristic method,called Fast insertion Tabu Search with Conflict-avoidance(FTS-C)heuristic,is developed.In the first stage,a conflict-avoidance insertion algorithm is designed to generate a high-quality initial solution by considering the requests transmission and download.Further,the tabu search-based second stage optimizes the initial solution.Finally,an extensive empirical study based on a real-world situation demonstrates that FTS-C can generate a solution with higher quality in less time than other state-of-the-art algorithms and the CPLEX solver.

A Mixed-integer SDP Solution to Distributionally Robust Unit Commitment with Second Order Moment Constraints

A power system unit commitment(UC)problem considering uncertainties of renewable energy sources is investigated in this paper,through a distributionally robust optimization approach.We assume that the first and second order moments of stochastic parameters can be inferred from historical data,and then employed to model the set of probability distributions.The resulting problem is a two-stage distributionally robust unit commitment with second order moment constraints,and it can be recast as a mixed-integer semidefinite programming(MI-SDP)with finite constraints.The solution algorithm of the problem comprises solving a series of relaxed MI-SDPs and a subroutine of feasibility checking and vertex generation.Based on the verification of strong duality of the semidefinite programming(SDP)problems,we propose a cutting plane algorithm for solving the MI-SDPs;we also introduce an SDP relaxation for the feasibility checking problem,which is an intractable biconvex optimization.Experimental results on the IEEE 6-bus system are presented,showing that without any tuning of parameters,the real-time operation cost of distributionally robust UC method outperforms those of deterministic UC and two-stage robust UC methods in general,and our method also enjoys higher reliability of dispatch operation.