Binary nonlinearization of the super classical-Boussinesq hierarchy

The symmetry constraint and binary nonlinearization of Lax pairs for the super classical-Boussinesq hierarchy is obtained. Under the obtained symmetry constraint, the n-th flow of the super classical-Boussinesq hierarchy is decomposed into two super finite-dimensional integrable Hamiltonian systems, defined over the super-symmetry manifold with the corresponding dynamical variables x and tn. The integrals of motion required for Liouville integrability are explicitly given.

The Bargmann Symmetry Constraint and Binary Nonlinearization of the Super Dirac Systems

An explicit Bargmann symmetry constraint is computed and its associated binary nonlinearization of Lax pairs is carried out for the super Dirac systems. Under the obtained symmetry constraint, the n-th flow of the super Dirac hierarchy is decomposed into two super finite-diinensional integrable Hamiltonian systems, defined over the super- symmetry manifold R^4N{2N with the corresponding dynamical variables x and tn. The integrals of motion required for Liouville integrability are explicitly given.

Binary Nonlinearization of the Nonlinear Schr?dinger Equation Under an Implicit Symmetry Constraint

By modifying the procedure of binary nonlinearization for the AKNS spectral problem and its adjoint spectral problem under an implicit symmetry constraint, we obtain a finite dimensional system from the Lax pair of the nonlinear Schrodinger equation. We show that this system is a completely integrable Hamiltonian system.

Optimum Location of Field Hospitals for COVID-19: A Nonlinear Binary Metaheuristic Algorithm

Determining the optimum location of facilities is critical in many fields,particularly in healthcare.This study proposes the application of a suitable location model for field hospitals during the novel coronavirus 2019(COVID-19)pandemic.The used model is the most appropriate among the three most common location models utilized to solve healthcare problems(the set covering model,the maximal covering model,and the P-median model).The proposed nonlinear binary constrained model is a slight modification of the maximal covering model with a set of nonlinear constraints.The model is used to determine the optimum location of field hospitals for COVID-19 risk reduction.The designed mathematical model and the solution method are used to deploy field hospitals in eight governorates in Upper Egypt.In this case study,a discrete binary gaining–sharing knowledge-based optimization(DBGSK)algorithm is proposed.The DBGSK algorithm is based on how humans acquire and share knowledge throughout their life.The DBGSK algorithm mainly depends on two junior and senior binary stages.These two stages enable DBGSK to explore and exploit the search space efficiently and effectively,and thus it can solve problems in binary space.

Bellman Equation for Optimal Processes with Nonlinear Multi-Parametric Binary Dynamic System

A process represented by nonlinear multi-parametric binary dynamic system is investigated in this work. This process is characterized by the pseudo Boolean objective functional. Since the transfer functions on the process are Boolean functions, the optimal control problem related to the process can be solved by relating between the transfer functions and the objective functional. An analogue of Bellman function for the optimal control problem mentioned is defined and consequently suitable Bellman equation is constructed.

High-Order Binary Symmetry Constraints of a Liouville Integrable Hierarchy and Its Integrable Couplings

A 3 × 3 matrix spectral problem and a Liouville integrable hierarchy are constructed by designing a new subalgebra of loop algebra A^-2. Furthermore, high-order binary symmetry constraints of the corresponding hierarchy are obtained by using the binary nonlinearization method. Finally, according to another new subalgebra of loop algebra A^-2, its integrable couplings are established.

Component reallocation and system replacement maintenance based on availability and cost in series systems

Component reallocation(CR)is receiving increasing attention in many engineering systems with functionally interchangeable and unbalanced degradation components.This paper studies a CR and system replacement maintenance policy of series repairable systems,which undergoes minimal repairs for each emergency failure of components,and considers constant downtime and cost of minimal repair,CR and system replacement.Two binary mixed integer nonlinear programming models are respectively established to determine the assignment of CR,and the uptime right before CR and system replacement with the objective of minimizing the system average maintenance cost and maximizing the system availability.Further,we derive the optimal uptime right before system replacement with maximization of the system availability,and then give the relationship between the system availability and the component failure rate.Finally,numerical examples show that the CR and system replacement maintenance policy can effectively reduce the system average maintenance cost and improve the system availability,and further give the sensitivity analysis and insights of the CR and system replacement maintenance policy.

A Stochastic Flight Problem Simulation to Minimize Cost of Refuelling

Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses for airline activities.A nonlinear mixed binary mathematical programming model for the airline fuel task is presented to minimize the total cost of refueling in an entire flight route problem.The model is enhanced to include possible discounts in fuel prices,which are performed by adding dummy variables and some restrictive constraints,or by fitting a suitable distribution function that relates prices to purchased quantities.The obtained fuel plan explains exactly the amounts of fuel in gallons to be purchased from each airport considering tankering strategy while minimizing the pertinent cost of the whole flight route.The relation between the amount of extra burnt fuel taken through tinkering strategy and the total flight time is also considered.A case study is introduced for a certain flight rotation in domestic US air transport route.The mathematical model including stepped discounted fuel prices is formulated.The problem has a stochastic nature as the total flight time is a random variable,the stochastic nature of the problem is realistic and more appropriate than the deterministic case.The stochastic style of the problem is simulated by introducing a suitable probability distribution for the flight time duration and generating enough number of runs to mimic the probabilistic real situation.Many similar real application problems are modelled as nonlinear mixed binary ones that are difficult to handle by exact methods.Therefore,metaheuristic approaches are widely used in treating such different optimization tasks.In this paper,a gaining sharing knowledge-based procedure is used to handle the mathematical model.The algorithm basically based on the process of gaining and sharing knowledge throughout the human lifetime.The generated simulation runs of the example are solved using the proposed algorithm,and the resulting distribution outputs for the optimum purchased fuel amounts from each airport and for the total cost and are obtained.

All-optical conversion scheme from binary to its MTN form with the help of nonlinear material based tree-net architecture

In the field of optical computing and parallel information processing, several number systems have been used for different arithmetic and algebraic operations. Therefore an efficient conversion scheme from one number system to another is very important. Modified trinary number （MTN） has already taken a significant role towards carry and borrow free arithmetic operations. In this communication, we propose a tree-net architecture based all optical conversion scheme from binary number to its MTN form. Optical switch using nonlinear material （NLM） plays an important role.

An Integrable Symplectic Map of a Differential-Difference Hierarchy

By choosing a discrete matrix spectral problem, a hierarchy of integrable differential-difference equations is derived from the discrete zero curvature equation, and the Hamiltonian structures are built. Through a higher-order Bargmann symmetry constraint, the spatial part and the temporal part of the Lax pairs and adjoint Lax pairs, which we obtained are respectively nonlinearized into a new integrable symplectic map and a finite-dimensional integrable Hamiltonian system in Liouville sense.

A NEW INTEGRABLE SYMPLECTIC MAP ASSOCIATED WITH A DISCRETE MATRIX SPECTRAL PROBLEM

A hierarchy of lattice soliton equations is derived from a discrete matrix spectral problem. It is shown that the resulting lattice soliton equations are all discrete Liouville integrable systems. A new integrable symplectic map and a family of finite-dimensional integrable systems are given by the binary nonli-nearization method. The binary Bargmann constraint gives rise to a Backlund transformation for the resulting lattice soliton equations.