Towards a Better System for Immigration Control

We study different methods of immigration control using a simple model of a congested world. Our main comparison involves quota, the predominant instrument of immigration control, and a proposed system of immigration tolls and emigration subsidies. We show that the equilibrium of the proposed system is Pareto superior to the quota system. This is consistent with the tolls and subsidies creating a market for international migrants. When countries are price-takers the market becomes perfect and the exploitation of gains from trade complete. From a normative perspective, an open-borders policy is preferred to both control methods but will meet political opposition because it hurts the residents of the rich country.

Nano-engineered hierarchical natural fibre composites with localised cellulose nanocrystals and tailored interphase for improved mechanical properties

Natural fibre composites have been utilised in many applications such as automotive and buildings, thanks to their high specific properties and environmentally friendly nature. However, the incompatibility between hydrophilic natural fibres and hydrophobic polymer resins remains a longstanding issue in natural fibre composites. Inspired by nature's hierarchical structures and tailored functionalities, a nano-engineered hierarchical natural fibre composite has been developed in this study, utilising cellulose nanocrystals (CNCs) as localised nano-reinforcements at flax surfaces in a flax/bio-epoxy system. A simple and versatile spray coating technique was used to deposit CNCs on unmodified flax fibres, without using any chemical solvents. With the increased surface roughness and hence improved epoxy wetting on nano-engineered flax surfaces (3 wt% CNC loading), mechanical properties of the hierarchical composites have been significantly improved, with a 60 % increase in interlaminar shear strength, indicating an enhanced interfacial load transfer between flax and epoxy, alongside improved flexural modulus (14 %) and strength (23 %). This green approach without using any chemicals provides a scalable and sustainable way to develop tailored interfaces for natural fibre composites with enhanced resin wetting and mechanical properties

Integrated Planning of Industrial Gas Supply Chains

In this work, we propose a Mixed Integer Linear Programming (MILP) model for optimal planning of industrial gas supply chain, which integrates supply contracts, production scheduling, truck and rail-car scheduling, as well as inventory management under the Vendor Managed Inventory (VMI) paradigm. The objective used here is minimisation of the total operating cost consisting of purchasing of raw material, production, and transportation costs by trucks/rail-cars so as to satisfy customer demands over a given time horizon. The key decisions for production sites include production schedule and purchase schedule of raw material, while the distribution decisions involve customer to plant/depot allocation, quantity transported through rail network, truck delivery amounts, and times. In addition, a relaxation approach is proposed to solve the problem efficiently. An industrial case study is evaluated to illustrate the applicability of the integrated optimisation framework

Hierarchical Approach to Integrated Planning of Industrial Gas Supply Chains

In this article, an optimization-based framework is proposed for integrated production and distribution planning of industrial gas supply chains. The main goal is to minimize the overall cost, which is composed of raw material, product sourced from external suppliers, production, truck, and rail-car costs, while satisfying customer demands. The overall problem is formulated as a mixed-integer linear programming (MILP) model while a two-phase hierarchical solution strategy is developed to solve the resulting optimization problem efficiently. The first phase relies on truck scheduling decisions being relaxed, whereas the second phase solves the original model at reduced space by fixing product allocation as determined by phase one. Finally, an industrial-size case study is used to illustrate the applicability and efficiency of the proposed optimization framework

Fair design of CCS infrastructure for power plants in Qatar under carbon trading scheme

Qatar is currently the highest emitter per capita and targets emission reduction by exercising tight controls on gas flaring. In order to limit the emission under allowances, the power plants have two options: investing in carbon capture and storage (CCS) systems or buying carbon credits for the excess emissions above their allowances. However, CCS systems are expensive for installation and operation. In this paper, a mixed integer linear programming (MILP) model is developed for the design of integrated carbon capture, transport and storage infrastructure in Qatar under carbon trading scheme. We first investigate the critical carbon credit prices to decide under which price it is more beneficial to invest on CCS systems or to buy carbon credits via carbon trading. Then the fair design of the CCS infrastructure is obtained under two fairness scenarios: the same saving ratio and the game theory Nash approach. Fair cost distribution among power plants in Qatar is obtained by selecting the CO2 resources (power plants) to be captured with available capture technologies and materials, designing the transportation pipeline network to connect the resources with the sequestration and/or utilisation sites and determining the carbon trading price and amount among power plants. Under different fairness scenarios, the total costs are slightly higher than that from minimising the total cost to obtain the fair cost distribution. Power plants with higher CO2 emissions determine to install CCS system, while other power plants buy the carbon credits from domestic or international market to fulfil their carbon allowance requirements. The future work includes extending the current model by considering power generation distribution and designing the pipeline network with the selection of pump locations and pipe diameters

Real-time freeway network traffic surveillance: large-scale field testing results in Southern Italy

This paper reports on some large-scale field-testing results of a real-time freeway network traffic surveillance tool that has recently been developed to enable a number of real-time traffic surveillance tasks. This paper first introduces the related network traffic flow model and the approaches employed to traffic state estimation, traffic state prediction, and incident alarm. The field testing of the tool for these surveillance tasks in the A3 freeway of 100 km between Naples and Salerno in southern Italy is then reported in some detail. The results obtained are quite satisfactory and promising for further future implementations of the tool

Integrated production and inventory routing planning of oxygen supply chains

In this work, we address a production and inventory routing problem for a liquid oxygen supply chain comprising production facilities, distribution network, and distribution resources. The key decisions of the problem involve production levels of production plants, delivery schedule and routing through heterogeneous vehicles, and inventory strategies for national stock-out prevention. Due to the problem complexity, we propose a two-level hybrid solution approach that solves the problem using both exact and metaheuristic methods. At the upper level, we develop a mixed-integer linear programming (MILP) model that determines production and inventory decisions and customer allocation. In the lower level, the original problem is reduced to several multi-trip heterogeneous vehicle routing problems by fixing the optimal production, inventory, and allocation decisions and clustering customers. A well-recognised metaheuristic, guided local search method, is adapted to solve the low-level routing problems. A real-world case study in the UK illustrates the applicability and effectiveness of the proposed optimisation framework