Dynamic flux balance analysis (DFBA) provides a platform for detailed design, control and optimization of biochemical process technologies. It is promising modeling framework that combines genome-scale metabolic network with dynamic simulation the extracellular environment. assumes intracellular species concentrations are in equilibrium The resulting underdetermined stoichiometric model solved under assumption objective such as growth rate maximization. metabolism coupled mass equations...

The determination of vehicle routes fulfilling connectivity, time, and operational constraints is a well-studied combinatorial optimization problem. NP-hard complexity routing problems has fostered the adoption tailored exact approaches, matheuristics, metaheuristics on classical computing devices. ongoing evolution quantum hardware recent advances algorithms (i.e., VQE, QAOA, ADMM) for mathematical programming make decision-making an avenue research worthwhile to be explored In this...

Abstract Quantum computing has been attracting public attention recently. This interest is driven by the advancements in hardware, software, and algorithms required for its successful usage promise that it entails potential acceleration of computational tasks compared to classical computing. perspective article presents a short review on quantum computing, how this approach solves problems, three fields can potentially impact most while relevant chemical engineering: chemistry, optimization,...

Accurate simulations of vibrational molecular spectra are expensive on conventional computers. Compared to the electronic structure problem, problem with quantum computers is less investigated. In this work we accurately estimate resources, such as number logical qubits and gates, required for calculations a programmable computer. Our approach based phase estimation focuses fault-tolerant devices. addition asymptotic estimates generic chemical compounds, present more detailed analysis...

The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm for finding the minimum eigenvalue of Hamiltonian that involves optimization parameterized circuit. Since resulting problem in general nonconvex, method can converge to suboptimal parameter values do not yield eigenvalue. In this work, we address shortcoming by adopting concept adiabatic computing (VAQC) as procedure improve VQE. VAQC, ground state continuously approximated via We discuss some basic theory VAQC...

Quantum chemistry applications on quantum computers currently rely heavily the variational eigensolver (VQE) algorithm. This hybrid quantum-classical algorithm aims at finding ground-state solutions of molecular systems based principle. VQE calculations can be systematically implemented for perturbations to each degree freedom, generating a Born-Oppenheimer potential-energy surface (PES) molecule. The PES then used derive thermodynamic properties, which are often desirable in chemical...

This work considers the computation of rigorous componentwise time-varying bounds on states a non-linear control system. develops new implementation an existing bounding theory that exploits physical information to produce tight bounds. It is shown solution certain initial value problem in ordinary differential equations (ODEs) depending parametric linear programs (LPs) (which are said be ‘embedded’) yields To ensure numerical tractability such formulation, some properties resulting system...

This work presents a numerical method for evaluating affine relaxations of the solutions parametric ordinary differential equations. is derived from general theory construction polyhedral outer approximation reachable set (“polyhedral bounds”) constrained dynamic system subject to uncertain time-varying inputs and initial conditions. an extension inequality-based comparison theorems. The new relaxation capable incorporating information simultaneously constructed interval bounds as well other...

Accurate simulations of vibrational molecular spectra are expensive on conventional computers. Compared to the electronic structure problem, problem with quantum computers is less investigated. In this work we accurately estimate resources, such as number qubits and gates, required for calculations a programmable computer. Our approach based phase estimation focuses fault-tolerant devices. addition asymptotic estimates generic chemical compounds, present more detailed analysis resources...

The reformulation of generalized semi-infinite programs (GSIP) to simpler problems is considered. These reformulations are achieved under the assumption that a duality property holds for lower level program (LLP). Lagrangian used in general case establish relationship between GSIP and related (SIP). Practical aspects this reformulation, including how bound multipliers, also This SIP result then combined with recent advances global, feasible solution develop point method GSIP. Reformulations...

Solution methods for generalized Nash equilibrium have been dominated by variational inequalities and complementarity problems. Since these approaches fundamentally rely on the sufficiency of first-order optimality conditions players' decision problems, they only apply as heuristic when players are modeled nonconvex optimization In contrast, this work using theory global bilevel programs. Through perspective, we draw precise connections between equilibria, feasibility programming,...

Generalized semi-infinite programs (GSIP) are a class of mathematical optimization problems that generalize programs, which have finite number decision variables and infinite constraints. Mitsos et al. (Mitsos Tsoukalas. "Global generalized via restriction the right hand side." Journal Global Optimization 61.1 (2015): 1-17.) present method for global GSIP. This involves lower bounding method, they claim these bounds converge to optimal objective value A counterexample is presented shows this false.