Use of Operations Research in Courier Delivery Services

Courier delivery services are used worldwide by millions of people. The scope of this field is wide. The services provided by most companies in this field is more or less the same. What sets them apart is the optimisation of resources and how these companies reduce their transportation cost while providing good service. While finding the best route, companies often blind side other factors and only focus on the shortest route. This paper is focused on Vehicle Routing Problem and its variations. It also talks about the current Softwares being used in this field

Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey

Over the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning tools on large-scale nonlinear monitoring and control problems. This article provides a survey of recent results with applications in the process industry.Comment: IFAC World Congress 202

Interval enclosures for reachable sets of chemical kinetic flow systems. Part 1: Sparse transformation

Computing reachable sets for continuous-stirred tank reactors (CSTRs) under uncertainty is crucial for designing efficient model-based control strategies or developing robust process monitoring protocols. This paper, the first in the three-part series, develops a linear transformation to project the dynamics of a CSTR reaction system onto a transformed state space. The proposed transformation is invertible, and leads to a “sparse” system representation in the transformed state space – a property crucial for the methods developed to compute reachable sets of CSTR reaction systems. The second and third papers in this series discuss how the transformation developed here can be used to compute effectively outer interval approximations to the reachable sets of CSTR reaction systems. To this effect, two new bounding methods – direct and indirect-bounding methods – are proposed in the second and third paper, respectively, to compute tight interval enclosures for the reachable sets of CSTR reaction systems. Several numerical examples are also provided to demonstrate efficacy of the proposed direct and indirect-bounding methods

Interval enclosures for reachable sets of chemical kinetic flow systems. Part 3: Indirect-bounding method

In the third paper, in the three-part series, we propose an indirect-bounding approach for constructing rigorous interval enclosures or bounds for the reachable sets of CSTR reaction systems subject to parametric and initial condition uncertainties and flow rate disturbances. Existing comparison-based methods yield conservative enclosures for the reachable sets due to the non-quasi-monotonic and non-cooperative nature of CSTR reaction systems. The proposed indirect-bounding method addresses the overestimation problem by using the isomorphic transformation, developed in Tulsyan and Barton (2017a), to map the system into a transformed state space, where comparison-based methods yield tight bounds. The interval bounds on the original states are then reconstructed using the inverse transformation. This eliminates the need to know a priori an effective enclosure set for the CSTR reaction system, as required by the direct-bounding method in Tulsyan and Barton (2017b). The efficacy of the indirect-bounding method is validated on several example problems. Several comparisons with the direct-bounding method are also presented to demonstrate the improvements achieved with the indirect-bounding method