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This paper establishes new convergence results for the power penalty method for a mixed complementarity problem(MiCP). The power penalty method approximates the MiCP by a nonlinear equation containing a power penalty term. The main merit of the method is that it has an exponential convergence rate with the penalty parameter when the involved function is continuous and ξ--monotone. Under the same assumptions, we establish a new upper bound for the approximation error of the solution to the nonlinear equation. We also prove that the penalty method can handle general monotone MiCPs. Then the method is used to solve a class of linearly constrained variational inequality(VI). Since the MiCP associated with a linearly constrained VI does not ξ--monotone even if the VI is ξ--monotone, we establish the new convergence result for this MiCP. We use the method to solve the asymmetric traffic assignment problem which can be reformulated as a class of linearly constrained VI. Numerical results are provided to demonstrate the efficiency of the method. [ABSTRACT FROM AUTHOR]

Aiming at the characteristics that the signal noise ratio (SNR) gradually decreases from the near to far range of the swath, an adaptive phase filtering algorithm based on Goldstein filtering and combined with multiple quality-guided graphs was proposed. Firstly, the components used to determine the filtering parameters were obtained through residue density, pseudo-coherence coefficient and pseudo-SNR, the three quality-guided graphs. Then, the filter parameters were calculated by weighting the three components. Finally, the size of filtering window was determined according to the account of residues, and the interferometric phase noise was removed in frequency domain. Simulated data, TSX/TDX data and airborne interferometric imaging radar altimeter data were used to verify the performance of the new algorithm. Compared with the results of Goldstein filtering and its improved algorithms, the results showed that the proposed algorithm can effectively filter out phase noise while maintaining the edge characteristics of interferometric fringe. The section of filtering result can well match with the section of simulated pure interfeometric phase. Moreover, the algorithm proposed in this paper can effectively remove the noise in the interferogram of TSX/TDX sea ice data, and the residues' filtering rate was above 86%, which can effectively remove the phase residues of the sea ice surface while maintaining the characteristics of the sea ice edge. Experimental results showed that the new algorithm provides an effective phase noise filtering method for imaging radar altimeter data processing. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the coordination of a supply chain consisting of one manufacturer andnBertrand competing retailers under disruptions of market demand and production cost. We present a coordination model of a supply chain under normal scenarios. Our findings demonstrate that the coordination scheme designed for the initial production plan should be revised when disruptions of market demand and production cost occur. To resolve this issue, we consider the possible deviation costs caused by disruptions and propose optimal decision models for different disruptions under centralised decision-making. We present an improved revenue-sharing contract model to coordinate the decentralised supply chain under disruptions. The proposed models are then further analysed through numerical examples. [ABSTRACT FROM AUTHOR]

This paper examines optimal decisions and coordination models for a dual-channel supply chain when the two end competition market demands are simultaneously disrupted. Firstly, we developed the pricing and production decisions models without demand disruptions and propose a revenue sharing contract to coordinate the dual-channel supply chain where the manufacturer is a Stackelberg leader and the retailer is a follower. We derived the conditions under which the maximum profit can be achieved in detailed. We compared the profits under normal case and disrupted case and quantified the information value of knowing demand disruptions. We proposed an improved revenue sharing contract to coordinate the dual-channel supply chain with demand disruptions. The results indicate that the adjusting prices and production quantity are the optimal decisions whether the demand disruptions case or normal case. We also find that the original revenue sharing contract is a special case of improved revenue sharing contract and the market scale change, channel substitutability and deviation cost affected the improved revenue sharing contract under demand disruptions. Finally, we further conduct numerical experiments to show how the demand disruption affects the decisions. [ABSTRACT FROM AUTHOR]