Planning and scheduling of a multipurpose batch chemical plant is always affected by uncertain factors, and one of them is the processing time of tasks. When the processing time deviates from its nominal value, the original production target …

This paper expands the multiparametric quadratic programming (mp-QP) framework presented in Narciso et al. (Comput Chem Eng 164:107882, 2022. https://doi.org/10.1016/j.compchemeng.2022.107882 ) to the more general multiparametric nonlinear …

Phononic crystals with tunable bandgap characteristics have attracted increasing research interest. In order to design the widest tunable bandgap, a magnetorheological elastomer phononic crystal plate (MREPCP) was developed and a topology …

In this work, we give a generalized formulation of the Black–Scholes model. The novelty resides in considering the Black–Scholes model to be valid on ’average’, but such that the pointwise option price dynamics depends on a measure representing …

Conventional knowledge graph completion methods are effective for completing knowledge graphs (KGs), but they face significant challenges when dealing with relations with only a limited number of associative triples. To address the issue of …

In this paper we define a fractional Sturm–Liouville problem (FSLP) on [0, 1] subject to dirichlet boundary condition. First we discretize FSLP to obtain the corresponding matrix eigenvalue problem (MEP) of finite order N. In direct problem we …

We propose an ensemble artificial neural network (EANN) methodology for predicting the day ahead energy demand of a district heating operator (DHO). Specifically, at the end of one day, we forecast the energy demand for each of the 24 h of the …

Dry bulk shipping plays a crucial role in intercontinental bulk cargo transport, with operators managing fleets to meet shippers’ transportation demand. A primary challenge for these operators is making optimal operational decisions about ship …

In this paper, we present a regularized dynamical system method for solving monotone inverse variational inequalities (IVIs) in infinite dimensional Hilbert spaces. It is shown that the corresponding Cauchy problem admits a unique strong global …

As climate change provides impetus for investing in smart cities, with electrified public transit systems, we consider electric public transportation buses in an urban area, which play a role in the power system operations in addition to their …

This paper describes a simple, but effective sampling method for optimizing and learning a discrete approximation (or surrogate) of a multi-dimensional function along a one-dimensional line segment of interest. The method does not rely on …

Aerodynamic performance of a semi-submerged inlet exposed to a significant amount of boundary layer ingestion is optimized using the open-source flow and adjoint solver SU2. Pressure recovery is taken as the objective function. Mass flow rate and …

Many design optimization problems include constraints to prevent intersection of the geometric shape being optimized with other objects or with domain boundaries. When applying gradient-based optimization to such problems, the constraint function …

Optimization problems with discrete–continuous decisions are traditionally modeled in algebraic form via (non)linear mixed-integer programming. A more systematic approach to modeling such systems is to use generalized disjunctive programming …

Many real-world application problems encountered in industry have no analytical formulation, that is they are blackbox optimization problems, and often make use of expensive numerical simulations. We propose a new blackbox optimization algorithm …

This paper develops an optimization model for determining the placement of switches, tie lines, and underground cables in order to enhance the reliability of an electric power distribution system. A central novelty in the model is the inclusion of …

Long-term block scheduling is a challenging problem that involves determining the best extraction period for blocks to maximize the net present value of the open-pit mining business. This process involves multiple constraints, mainly ensuring safe …

The primal-dual interior-point method is widely recognized as one of the most effective approaches for solving the linear complementarity problem. As an extension of the linear complementarity problem, the study of the weighted linear …

This paper studies the dual relation between risk-sensitive control and large deviation control of maximizing the probability for out-performing a target for Markov Decision Processes. To derive the desired duality, we apply a non-linear extension …

Spreading processes on networks (graphs) have become ubiquitous in modern society with prominent examples such as infections, rumors, excitations, contaminations, or disturbances. Finding the source of such processes based on observations is …