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Abstract: The purpose of this paper is to introduce the notion of general -monotone operators in Banach spaces and the new proximal mapping associated with the general -monotone operators. By using Alber’s inequalities and the new proximal mapping technique, the variational convergence of a new proximal algorithm for nonlinear general -monotone operator equation systems with relaxed cocoercive operators in Banach spaces is introduced and studied. Our results improve and generalize the corresponding results of recent works. [Copyright &y& Elsevier]

This paper studies an intelligent maritime search and rescue (SAR) system problem. According to historical accidents and available SAR equipment information, a bi-level mixed-integer programming (MIP) model is proposed to determine the type and number of SAR equipment allocated to activated stations. Particle swarm optimization (PSO) algorithm and genetic algorithm (GA) algorithm are applied to solve the proposed mathematical model. Computational experiments based on real instances in the East Sea China not only validate the effectiveness of the bi-level MIP model in balancing two objectives during decision process, but also indicate that PSO algorithm is better than GA algorithm to solve the proposed model and generate reasonable equipment allocation plans. Some managerial implications are also outlined on the basis of the numerical experiments. [ABSTRACT FROM AUTHOR]

This paper introduces a mixed-integer nonlinear programming (MINLP) model aimed at designing a dependable closed-loop supply chain that can function effectively despite disruptions. The model incorporates several strategies to reduce the risks associated with random facility disruptions. First, the concept of p -robustness criterion is employed, which sets upper bounds on the cost in various disruption scenarios to protect against disruptions. To accommodate for the varying levels of reliability of facilities, the network consists of two categories of infrastructure: reliable and defective hybrid infrastructure. Thirdly, a sharing strategy is proposed to mitigate for the capacity loss at unreliable facilities by permitting transportation of products from reliable facilities to unreliable facilities. Additionally, an improved genetic algorithm (IGA) is devised for the MINLP model efficiently. The efficacy of the model and the tailored algorithm is evaluated by means of computational experiments. Finally, a sensitivity analysis is ultimately performed to furnish managers with meaningful insights. For example, the sharing strategies demonstrate a significant decrease of total cost. This paper contributes to enhancing resilience in logistics networks, ensuring their reliable performance even in the face of disruptions. [ABSTRACT FROM AUTHOR]