On the Robust and Stable Flowshop Scheduling Under Stochastic and Dynamic Disruptions

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Xie

et al. 2018

Self Cite

Energy has been increasingly generated or collected by different entities on the power grid (e.g., universities, hospitals and householdes) via solar panels, wind turbines or local generators in the past decade. With local energy, such electricity consumers can be considered as "microgrids" which can simulataneously generate and consume energy. Some microgrids may have excessive energy that can be shared to other power consumers on the grid. To this end, all the entities have to share their local private information (e.g., their local demand, local supply and power quality data) to each other or a third-party to find and implement the optimal energy sharing solution. However, such process is constrained by privacy concerns raised by the microgrids. In this paper, we propose a privacy preserving scheme for all the microgrids which can securely implement their energy sharing against both semihonest and colluding adversaries. The proposed approach includes two secure communication protocols that can ensure quantified privacy leakage and handle collusions.

Section: Discussionmentioning

confidence: 99%

Privacy Preserving and Collusion Resistant Energy Sharing

Yuan

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Xie

et al. 2018

Self Cite

“…From the perspective of biobjective optimization, evolutionary multiobjective optimization (EMO) algorithm returns at one time a set of nondominated solutions [41][42][43], i.e., the Pareto front, for the decision-maker's reference. We propose two strategies to improve the multiobjective memetic algorithm (MOMA) which has successfully solved many difficult numerical optimization problems and outperforms NSGA-II (the nondominated sorting genetic algorithm) and SPEA2 (the improved strength Pareto evolutionary algorithm) for the 7 Complexity two-objective and three-objective benchmark flow shop scheduling instances [44].…”

Section: 4mentioning

confidence: 99%

“…Its key operators include selection, crossover, and mutation. We apply the tournament selection operator (see the details in [44]). According to Ishibuchi et al [45], the two-point crossover and insertion mutation operators are adopted.…”

Section: 4mentioning

confidence: 99%

“…For large-size problems, the termination of the proposed MOMA algorithm is controlled by setting a running time limit of 100 seconds. In order to verify the effectiveness and efficiency, the MOMA is compared with several state-of-the-art EMO algorithms [44], including the hybrid quantum-inspired genetic algorithm (HQGA), the hybrid particle swarm optimization algorithm (HPSO), the hybrid simulated annealing algorithm (HSA), the multiobjective evolutionary algorithm based on decomposition (MOEA/ D), and NSGA-II. The parameters of the above algorithms are taken from Liu et al [44].…”

Section: Computational Studymentioning

confidence: 99%

See 1 more Smart Citation

Bicriterion Optimization for Flow Shop with a Learning Effect Subject to Release Dates

Yang

2018

Complexity

This paper investigates a two-machine flow shop problem with release dates in which the job processing times are variable according to a learning effect. The bicriterion is to minimize the weighted sum of makespan and total completion time subject to release dates. We develop a branch-and-bound (B&B) algorithm to solve the problem by using a dominance property, several lower bounds, and an upper bound to speed up the elimination process of the search tree. We further propose a multiobjective memetic algorithm (MOMA), enhanced by an initialization strategy and a global search strategy, to obtain the Pareto front of the problem. Computational experiments are also carried out to examine the effectiveness and the efficiency of the B&B algorithm and the MOMA algorithm.

“…Ansari [5] took covariance as a solution robustness criterion and measured the robustness of the schedule obtained by simulations and the critical chain method. Liu [6] established a robustness criterion using a time slack-based technique to deal with schedules with mechanical malfunction and new job arrivals. Xiao [7] took the expected relative deviation between the planned and actual schedule as a solution robustness criterion and used the criterion to analyze the robustness of the stochastic job shop scheduling problem.…”

Section: Introductionmentioning

confidence: 99%

A Construction Schedule Robustness Measure Based on Improved Prospect Theory and the Copula-CRITIC Method

Zhao

et al. 2020

Applied Sciences

A robustness measure is an effective tool to evaluate the anti-interference capacity of the construction schedule. However, most research focuses on solution robustness or quality robustness, and few consider a composite robustness criterion, neglecting the bounded rationality of subjective weights and inherent importance and nonlinear intercriteria correlations of objective weights. Therefore, a construction schedule robustness measure based on improved prospect theory and the Copula-criteria importance through intercriteria correlation (CRITIC) method is proposed. Firstly, a composite robustness criterion is established, including start time deviation rs and structural deviation rp for measuring solution robustness from project execution and completion probability rc for measuring quality robustness from the project result. Secondly, bounded rationality is considered, using prospect theory to calculate subjective weights, which is improved by the interval distance formula. Thirdly, the Copula-CRITIC method is proposed to determine objective weights incorporating both inherent importance and nonlinear intercriteria correlations. Finally, an information-entropy-based evidence reasoning method is applied to combine subjective and objective weights together while identifying their validity. An underground power station in China is used for a case study, whose robustness is measured using the proposed methods, single robustness criterion, and composite robustness criterion using traditional weighting methods. The comparison results verify the consistency, representativeness, and advantage of the proposed criterion and methods.