Horizon Framework Research Articles

Integration of inter-terminal transport and hinterland rail transport

This paper investigates the problem of inter-terminal movements of containers and vehicles within a port area in order to achieve an integrated and effective transport within the port and towards the hinterland. Containers from different port terminals are first moved to a rail yard and then delivered to the hinterland by rail. To provide insights for stakeholders such as port authority and terminal operators into tactical planning problems, e.g., the coordination between terminals, railway timetable and train sizes, this paper proposes an optimization model describing the movement of containers and various vehicles between and inside terminals. The model aims at improving the container delivery from container terminals to the hinterland considering both railway hinterland transport and terminal handling operations. A network inspired by a real-life port area and its hinterland is used as a test case to test different components, i.e., inter-terminal transport connections, train formation, railway timetable. A rolling horizon framework is used to improve the computation efficiency in large transport demand cases. The result of the optimization helps in identifying the most promising features, namely, that more connections between terminals and a flexible outbound railway timetable could contribute to improving the integrated container transport performance.

Approximate analytical solutions for consumption/investment problems under recursive utility and finite horizon

We study the asset allocation and consumption decisions of an investor with recursive utility and a finite investment horizon. We provide an approximate analytical solution under a stochastic investment opportunity set. The solution becomes exact when the elasticity of intertemporal substitution is equal to one or under a constant opportunity set. We show that this elasticity impacts both consumption and portfolio strategies, indicating the importance of disentangling intertemporal substitution from risk aversion. The investor’s horizon also plays a crucial role in optimal policies and the usual infinite horizon framework is inappropriate for investors having short- or medium-term horizons. Moreover, the infinite horizon problem reveals the existence of conditions on the preference parameters for our solution to hold, raising the question of whether another solution may exist or not. On its turn, the absence of a bequest motive in the finite horizon problem imposes another condition on risk parameters.

Multi‐level, multi‐stage lot‐sizing and scheduling in the flexible flow shop with demand information updating

AbstractMotivated by a real‐world problem in an automobile manufacturing firm, we study the multi‐level, multi‐stage lot‐sizing and scheduling problem with demand information updating. The objective is to determine the quantities and sequences of production on different production stages to minimize the total costs of production and inventory. We employ the martingale model for forecast evolution to model the evolving demand over time and build a mixed‐integer programing (MIP) model for the problem using a hybrid period approach (i.e., combining micro‐ and macro‐periods). To solve this NP‐hard problem, we propose three heuristic algorithms based on the idea of “relax‐and‐fix” within the rolling horizon framework. We conduct computational experiments to test the performance of the heuristic algorithms as well as compare the performance of the proposed heuristics with the benchmark procedure (truncated procedure for MIP) for both small‐ and large‐scale problem instances. The computational results show that Heuristic 1 performs the best among the three heuristic algorithms.

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Navigation architecture for hypersonic aircraft

This paper aims at presenting an integrated navigation algorithm designed for estimating the navigation state of the STRATOFLY vehicle (LAPCAT–MR3). STRATOFLY project has been funded by the European Commission, under the framework of Horizon 2020 plan, with the aim of assessing the potential of high–speed transport vehicle. The complex interaction between elements of an air-breathing hypersonic vehicle represents a new paradigm in aircraft design. In particular, one of the needs for early GNC analysis in the case of LAPCAT–MR3 vehicle is the assessment of navigation performance over the reference trajectory. The navigation algorithm presented in this paper is based on an augmented state EKF data fusion algorithm exploiting inertial measurements provided by gyroscopes and accelerometers, heading estimates provided by a magnetometer and satellite-based measurements provided by a spaceborne GNSS receiver, considering GPS, GLONASS and GALILEO constellations.

Effect of control surfaces on the aerodynamic database of the Stratofly hypersonic vehicle

This paper aims at studying the control surfaces of the STRATOFLY project reference aircraft, funded by the European Commission, under the framework of Horizon 2020 plan. The values of aerodynamic coefficients in a wide range of flow free-stream conditions are stored in the aircraft aerodynamic database. The research goal is to update a pre-existent database that was developed with fixed control surfaces using the six control surfaces deflection as input. Different Mach numbers determine different flow regimes: subsonic, transonic, supersonic, and hypersonic. In subsonic, transonic and low supersonic regimes a vortex-lattice solver is used to obtain the global coefficients assuming an unviscous flow on a simplified model. In hypersonic flow a build-up approach is applied: the control surfaces deflection contribution is developed by assuming a two-dimensional flow on the airfoil and by applying shock-expansion theory on the geometry. Then the paper analyses results showing stability and L/D results. The final paragraph focuses on trimmability at cruise Mach. No trimmed solution is obtainable to optimize the propulsive system. The solution proposed to solve this issue is to extend the four elevons: larger elevons are found to be able to trim the vehicle at the desired angle of attack.

Same-Day Delivery with Crowdshipping and Store Fulfillment in Daily Operations

Abstract This paper examines the problem of daily operations of same-day delivery with crowdshipping and store fulfillment (SDD-CSF). We aim to close the last-mile delivery gap between local stores and customers. SDD-CSF makes order fulfillment plan from two aspects: order souring decision and delivery method selection in order to minimize the cost associated with the order fulfillment plan. We adopt the new concept of last-mile delivery from local stores using crowdsourced shipping, which includes two specific delivery methods based on the distinct characteristics of crowdsourced shippers: Information Sharing Driver (ISDs) and Occasional Drivers (ODs). We devise a dynamic programming model for order fulfillment in a rolling horizon framework, which later is mathematically approximated into a mixed integer linear programming model. The model considers both currently received orders and the predicted future demand to make order assignment decision that minimizes the immediate delivery cost plus the resulting future expected cost. It repeatedly solves the model following the timeline in order to construct an optimal fulfillment plan from local stores. With the help of the rolling horizon structure, we also introduce a feedback control system to cope with the inaccurate forecast of future demand. Finally, we prove that under perfect information, the proposed formulation can converge to the global optimum.

A Decision Support System for Proactive-Robust Traffic Network Management

Real-time traffic network management systems are envisioned to provide network operators with decision support capabilities to alleviate recurrent and non-recurrent congestion. These capabilities involve predicting the network congestion dynamics and facilitating the development of proactive traffic management schemes that integrate traffic control and demand management strategies. However, traffic networks are subject to numerous sources of stochasticity that make it difficult to accurately predict their operational conditions and generate effective traffic management schemes to cope with these conditions. This paper presents a decision support system for proactive-robust traffic network management, which accounts for uncertainty in the network operational conditions. The objective is to develop robust traffic management schemes such that the network overall performance remains close to optimality under all possible future operational conditions. The modeling framework of the system is presented, which adopts a rolling horizon framework that integrates a meta-heuristic search algorithm and a dynamic traffic assignment simulation-based methodology. The system performance is examined through application to the traffic network of the US-75 corridor in Dallas, TX, USA.

La linea stilistica della «chiarezza poetica» Comisso vs d’Annunzio

Giovanni Comisso, after d’Annunzio passed away, proposed to place his artistic figure in the framework of the contemporary critical horizon, selecting a very peculiar formal line, distinguished by ‘clarity’, in order to measure himself and, together, to take the necessary distances from the teaching of the ‘Vate’. In the second part of this paper, a Comissian critical essay is published, which appeared in the early ’60s in Il Mondo of Pannunzio and has remained in the shadows so far; in it we summarise an exemplary historiographical and stylistic balance of the Italian narrative between the 19th and the beginning of the 20th century, re-reading in perspective and under another way d’Annunzio’s function.

Vehicle routing with arrival time diversification

Unpredictable routes may be generated by varying the arrival time at each customer over successive visits. Inspired by a real-life case in cash distribution, this study presents an efficient solution approach for the vehicle routing problem with arrival time diversification by formulating it as a vehicle routing problem with multiple time windows in a rolling horizon framework. Because waiting times are not allowed, a novel algorithm is developed to efficiently determine whether routes or local search operations are time window feasible. To allow infeasible solutions during the heuristic search, four different penalty methods are proposed. The proposed algorithm and penalty methods are evaluated in a simple iterated granular tabu search that obtains new best-known solutions for all benchmark instances from the literature, decreasing average distance by 29% and reducing computation time by 93%. A case study is conducted to illustrate the practical relevance of the proposed model and to examine the trade-off between arrival time diversification and transportation cost.

Electricity Price Forecasting for Operational Scheduling of Behind-the-Meter Storage Systems

Electricity price forecast plays a key role in strategic behavior of participants in competitive electricity markets. With the growth of behind-the-meter energy storage, price forecasting becomes important in energy management and control of such small-scale storage systems. In this paper, a forecasting strategy is proposed for real-time electricity markets using publicly available market data. The proposed strategy uses high-resolution data along with hourly data as inputs of two separate forecasting models with different forecast horizons. Moreover, an intra-hour rolling horizon framework is proposed to provide accurate updates on price predictions. The proposed forecasting strategy has the capability to detect price spikes and capture severe price variations. The real data from Ontario's electricity market is used to evaluate the performance of the proposed forecasting strategy from the statistical point of view. The generated price forecasts are also applied to an optimization platform for operation scheduling of a battery energy storage system within a grid-connected micro-grid in Ontario to show the value of the proposed strategy from an economic perspective.

A new building envelope – increasing daylight and energy efficiency with water flow glazing

ABSTRACTBuilding industry is still chasing the dream of fully transparent glass facades. However, available technologies of today show severe contradictions to the main purpose of such fully glazed facades: on the one side, the clear and unobstructed view from the inside into the outside environment, on the other side enabling maximum daylight autonomy to the building users. The main reason is the inevitable requirement of solar protection to avoid solar heat gains and consequently high cooling capacities in buildings. Solar coatings, tinted glass, switchable windows and classic interior and exterior sun shading devices all have the same general effect: The quality of the views to the outside is reduced, the amount of available daylight decreases. The European Union has funded the project InDeWaG (Industrial Development of Water Flow Glazing Systems) within the framework of the European research program HORIZON 2020. During the research period of three and a half years the international consortium incorporating research institutes, industry and designers is developing a new insulation glass unit. In the cavity of this unit a water‐glycol mixture is circulating. Due to the spectral properties of water, it captures most of the infrared solar radiation: it is transparent to visible wavelengths of the sunlight but opaque to NIR wavelengths. Consequently, water flow glazing has the same natural light transmission as conventional glazing whilst reducing the heat transfer towards the interior space. Moreover, the water circulation allows to use, store or dissipate the energy captured by absorption of the waterfilled cavity.

Robustly stable adaptive horizon nonlinear model predictive control

We present a new method for adaptively updating nonlinear model predictive control (NMPC) horizon lengths online via nonlinear programming (NLP) sensitivity calculations. This approach depends on approximation of the infinite horizon problem via selection of terminal conditions, and therefore calculation of non-conservative terminal conditions is key. For this, we also present a new method for calculating terminal regions and costs based on the quasi-infinite horizon framework that extends to large-scale nonlinear systems. This is accomplished via bounds found through simulations under linear quadratic regulator (LQR) control. We show that the resulting controller is Input-to-State practically Stable (ISpS) with a stability constant that depends on the level of nonlinearity in the terminal region. Finally, we demonstrate this approach on a quad-tank system and a large-scale distillation application. Simulation results reveal that the proposed approach is able to achieve significant reduction in average computation time without much loss in the performance with reference to fixed horizon NMPC.

Rear Vehicle Tracking on a Bicycle Using Active Sensor Orientation Control

This paper focuses on the development of an active sensing system for a bicycle to accurately detect and track rear vehicles. A collision detection sensor on a bicycle is required to be inexpensive, small, and lightweight. A single beam laser sensor that meets these constraints is mounted on a rotationally controlled platform for this sensing mission. The rotational orientation of the laser sensor needs to be actively controlled in real time in order to continue to focus on a rear vehicle, as the vehicle’s lateral and longitudinal distances change. This tracking problem requires controlling the real-time angular position of the laser sensor without knowing the future trajectory of the vehicle. The challenge is addressed using a novel receding horizon framework for active control and an interacting multiple model framework for estimation. The features and benefits of this active sensing system are shown first using simulation results. Then, extensive experimental results are presented using an instrumented bicycle to show the performance of the system in detecting and tracking rear vehicles during both straight and turning maneuvers.

A data-driven optimal control approach for solution purification process

Solution purification holds a critical position in hydrometallurgy. With its inherent complexity and the mixed raw material supply, solution purification process exhibits various working conditions, and has nonlinear, time-varying dynamics. At current stage, a comprehensive and precise model of a solution purification process is still costly to obtain. More specifically, the model structure could be derived by applying physical and chemical principles, while the accurate model parameters cannot be obtained under certain working conditions due to reasons like insufficient data samples. This, in turn, introduces obstacles in achieving the optimal operation. In order to circumvent the modeling difficulty, this paper proposes a ‘Process State Space’ descriptive system to re-describe the optimal control problem of solution purification process, accordingly establishes a two-layer receding horizon framework for developing a data-driven optimal control of solution purification process. In the optimal control scheme, on the ‘optimization’ layer, by utilizing the ‘multiple-reactors’ characteristic of solution purification process, a ‘gradient’ optimization strategy is proposed to transform the dosage minimization problem into obtaining the optimal variation gradient of the outlet impurity concentrations along the reactors. On the ‘control’ layer, a model-free input constrained adaptive dynamic programming algorithm is devised and applied to calculate the optimal dosages for each reactor by learning from the real-time production data. Case studies are performed to illustrate the effectiveness and efficiency of the proposed approach. The results and problems need future research are also discussed.

Plan-based flexible bus bridging operation strategy

Bus bridging has been widely used to connect stations affected by metro disruptions such that stranded passengers could resume their journeys. Previous studies generally assumed that a bus operates exclusively on one bridging route with given frequency, which limits the service flexibility and reduce the operational efficiency. We propose a strategy to instruct buses to operate on predefined bridging routes once they are dispatched from depots. Buses are allowed to flexibly serve different bridging routes. Each bus operates based on a bridging plan that lists the stations to serve in sequence instead of route frequencies. A two-stage model is developed to optimize the bridging plans and their assignments to buses with the objectives that balance the operational priorities between minimizing bus bridging time and reducing passenger delay. A Weight Shortest Processing Time first (WSPT) rule based heuristic algorithm is developed to solve the proposed model. The developed model is further incorporated in a rolling horizon framework to handle dynamic passenger arrivals during the disruption period. The effectiveness of the proposed strategy is demonstrated in comparison with alternative strategies in real-world case studies.

Online low-field NMR spectroscopy for process control of an industrial lithiation reaction-automated data analysis.

Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential forenabling closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies. We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (indirect hard modeling-IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union's Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analyzed by IHM with low calibration effort, compared to a multivariate PLS-R (partial least squares regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy. Graphical abstract NMR sensor module for monitoring of the aromatic coupling of 1-fluoro-2-nitrobenzene (FNB) with aniline to 2-nitrodiphenylamine (NDPA) using lithium-bis(trimethylsilyl) amide (Li-HMDS) in continuous operation. Online 43.5 MHz low-field NMR (LF) was compared to 500 MHz high-field NMR spectroscopy (HF) as reference method.

An Optimal Investment Strategy for Insurers in Incomplete Markets

In this paper we consider the problem of an insurance company where the wealth of the insurer is described by a Cramér-Lundberg process. The insurer is allowed to invest in a risky asset with stochastic volatility subject to the influence of an economic factor and the remaining surplus in a bank account. The price of the risky asset and the economic factor are modeled by a system of correlated stochastic differential equations. In a finite horizon framework and assuming that the market is incomplete, we study the problem of maximizing the expected utility of terminal wealth. When the insurer’s preferences are exponential, an existence and uniqueness theorem is proven for the non-linear Hamilton-Jacobi-Bellman equation (HJB). The optimal strategy and the value function have been produced in closed form. In addition and in order to show the connection between the insurer’s decision and the correlation coefficient we present two numerical approaches: A Monte-Carlo method based on the stochastic representation of the solution of the insurer problem via Feynman-Kac’s formula, and a mixed Finite Difference Monte-Carlo one. Finally the results are presented in the case of Scott model.

Redesign strategies of a comprehensive robust relief network for disaster management

We address the problem of designing as well as redesigning a relief network over multiple periods as a strategic decision which plays a critical role in the post-disaster management. Design of the relief network has a significant impact on the effective performance of disaster response operations. For considering both the uncertainty and dynamism of the decision-making environment, a comprehensive scenario-based robust approach embedded in the rolling horizon framework is proposed. The proposed mixed-integer linear programming model is inspired by a real case study of a disaster management in Iran, which aims to minimize the total cost of network management. Furthermore, restorative strategies are considered to increase the efficiency and robustness of the proposed relief network under disaster. To tackle the proposed optimization model, a heuristic solution algorithm is adopted. The results indicate that the proposed robust relief network provides an affordable access to its demand points in a sustainable manner under disaster. In addition, extensive computational results illustrate the efficiency of the proposed model in dealing with the considered disaster management issues.

Human Rights of Senior People in Ukraine: Current Reality and European Perspectives

The article aims to provide a survey of the current situation with human rights of senior people in Ukraine, based on the legal analysis and sociological overview. The questionnaire for the overview was built to show the level of seniors’ knowledge about their rights and possible ways of protection, level seniors’ human rights infringement and awareness about possible remedies in case of infringement. The sample of the sociological overview includes 1 379 persons. The interviews were done by students under the supervision of the authors of this paper in the framework of GRAGE Horizon 2020 project. Sample analysis and calibration resulted in 1 159 valid respondents’ forms. The Gender structure of the responses constitutes 39 % women and 61 % men. The group includes people from 60 years old and older, including long-livers (90+). Seven main questions were put to the interviewed: Do you know which rights and benefits do older persons have in Ukraine? Do you know any NGOs or societies, which deal with older person’s rights protection? Do you meet information about older person’s rights in newspapers or TV programs? Have you ever been discriminated on the basis of your age (in the sphere of employment, credits, insurance etc.)? Have you ever experienced physical or psychological violence because of your age (from your relatives, social workers, and other people)? Which rights of older persons are the most violated? Do you know where to appeal in your city in case of your (as older person) rights are violated? The results of such analysis are represented in diagrams and show the real picture of seniors’ rights protection in Ukraine and proper ways of its improvement. Two main rights of elderly which are the subject of violation are the right to proper material support (low level of pensions) and the right to medical care (low level of healthcare support). But one of the main problems of seniors’ rights protection in Ukraine is the low level of elderly knowledge about their rights, ways of protection and possible remedies in the case of infringement. The authors provide their view on the reforming approaches to increase the life level of elderly in Ukraine based on the current development of European practice and achievements of GRAGE Horizon 2020 project. This work was supported by European Union’s Horizon 2020 research and innovation Programme under the Marie Sklodowska-Curie (grant no. 645706 (Project GRAGE). This paper reflects only the authors’ view and the REA is not responsible for any use that may be made of the information it contains.