Andrea Emilio Rizzoli

Selecting among five common modelling approaches for integrated environmental assessment and management

The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings. We review five common integrated modelling approaches.Model choice considers purpose, data type, scale and uncertainty treatment.We present a guiding framework for selecting the most appropriate approach.

Time dependent vehicle routing problem with a multi ant colony system

The Time Dependent Vehicle Routing Problem (TDVRP) consists in optimally routing a fleet of vehicles of fixed capacity when travel times are time dependent, in the sense that the time employed to traverse each given arc, depends on the time of the day the travel starts from its originating node. The optimization method consists in finding solutions that minimize two hierarchical objectives: the number of tours and the total travel time. Optimization of total travel time is a continuous optimization problem that in our approach is solved by discretizing the time space in a suitable number of subspaces. New time dependent local search procedures are also introduced, as well as conditions that guarantee that feasible moves are sought for in constant time. This variant of the classic Vehicle Routing Problem is motivated by the fact that in urban contexts variable traffic conditions play an essential role and can not be ignored in order to perform a realistic optimization. In this paper it is shown that when dealing with time constraints, like hard delivery time windows for customers, the known solutions for the classic case become unfeasible and the degree of unfeasibility increases with the variability of traffic conditions, while if no hard time constraints are present, the classic solutions become suboptimal. Finally an application of the model to a real case is presented. The model is integrated with a robust shortest path algorithm to compute time dependent paths between each customer pairs of the time dependent model.

Ant Colony System for a Dynamic Vehicle Routing Problem

An aboundant literature on vehicle routing problems is available. However, most of the work deals with static problems, where all data are known in advance, i.e. before the optimization has started.The technological advances of the last few years give rise to a new class of problems, namely the dynamic vehicle routing problems, where new orders are received as time progresses and must be dynamically incorporated into an evolving schedule.In this paper a dynamic vehicle routing problem is examined and a solving strategy, based on the Ant Colony System paradigm, is proposed.Some new public domain benchmark problems are defined, and the algorithm we propose is tested on them.Finally, the method we present is applied to a realistic case study, set up in the city of Lugano (Switzerland).

Progress in integrated assessment and modelling

Environmental processes have been modelled for decades. However. the need for integrated assessment and modeling (IAM) has,town as the extent and severity of environmental problems in the 21st Century worsens. The scale of IAM is not restricted to the global level as in climate change models, but includes local and regional models of environmental problems. This paper discusses various definitions of IAM and identifies five different types of integration that Lire needed for the effective solution of environmental problems. The future is then depicted in the form of two brief scenarios: one optimistic and one pessimistic. The current state of IAM is then briefly reviewed. The issues of complexity and validation in IAM are recognised as more complex than in traditional disciplinary approaches. Communication is identified as a central issue both internally among team members and externally with decision-makers. stakeholders and other scientists. Finally it is concluded that the process of integrated assessment and modelling is considered as important as the product for any particular project. By learning to work together and recognise the contribution of all team members and participants, it is believed that we will have a strong scientific and social basis to address the environmental problems of the 21st Century.

Simulation and planning of an intermodal container terminal

A decision support system for management of an intermodal container terminal is presented. Among problems to be solved are the spatial allo cation of containers in the terminal yard, the allo cation of resources, and the scheduling of opera tions to maximise a performance function based on economic indicators. These problems are solved using techniques from optimisation, such as job-shop scheduling, genetic algorithms or mixed-integer linear programming. At the termi nal, the same problems are usually solved by the terminal manager, using only his experience. The manager can trust computer-generated solutions only by validating them by means of a simulation model of the terminal. Thus, the simulation tool also becomes a means to introduce new ap proaches into traditional settings. We focus on the resource allocation problem and describe our modules for optimisation of the allocation process and the simulation of the terminal. The former is based on integer linear programming; the latter is a discrete-event simulation tool based on the pro cess-oriented paradigm. The simulator provides a testbed for checking the validity and robustness of the policy computed by the optimisation module.

Delivering environmental decision support systems: software tools and techniques

A suite of “desirable features” for Environmental Decision Support Systems (EDSS) is proposed by identifying the general attributes of environmental systems which are of importance to modelling and simulation, and the different categories of users of EDSSs. With these features as a guide, a review and discussion of the approaches to delivering Environmental Decision Support Systems is presented. The two most efficient approaches are: (i) the use of modelling and simulation software tools, and (ii) the use of model integration and re-use techniques. A review of the currently available software tools for environmental modelling and simulation is therefore presented, and an overview of the current research activities in model integration and re-use is provided. Numerous existing EDSS are used as examples of the different approaches throughout the review. The review highlights the advantages and disadvantages of the two main approaches to EDSS delivery, and subsequently discusses the role emerging information technologies may play in the future delivery of EDSS. The paper concludes that while the available software for modelling and simulation is very advanced, some of the desirable features of EDSS (such as representation of spatial data and provision of expert help) cannot be easily delivered using such software. While the research activities in model integration and re-use are making real advances, especially in delivering those features which cannot currently be provided using modelling and simulation software, this is not occurring in any coordinated or synergistic manner. The ultimate goal should be to provide a fully general EDSS development platform which would allow system analysts to develop EDSS for any environmental domain complete with all desirable features. This is still considered to be very much a long-term ambition.

An optimization methodology for intermodal terminal management

A solution to the problems of resource allocation and scheduling of loading and unloading operations in a container terminal is presented. The two problems are formulated and solved hierarchically. First, the solution of the resource allocation problem returns, over a number of work shifts, a set of quay cranes used to load and unload containers from the moored ships and the set of yard cranes to store those containers on the yard. Then, a scheduling problem is formulated to compute the loading and unloading lists of containers for each allocated crane. The feasibility of the solution is verified against a detailed, discrete-event based, simulation model of the terminal. The simulation results show that the optimized resource allocation, which reduces the costs by [frac13], can be effectively adopted in combination with the optimized loading and unloading list. Moreover, the simulation shows that the optimized lists reduce the number of crane conflicts on the yard and the average length of the truck queues in the terminal.

A simulation tool for combined rail/road transport in intermodal terminals

A simulation model of the flow of intermodal terminal units (ITUs) among and within inland intermodal terminals is presented. The intermodal terminals are interconnected by rail corridors. Each terminal serves a user catchment area via a road network. The terminal is modelled as a set of platforms, which are served by a number of gantry cranes and front lifters. The user of the simulation model defines the structure of the terminal and the train and truck arrival scenarios. The train arrivals are defined in a train timetable, while the patterns of truck arrivals for ITU delivery and pick-up can be either statistically modelled or given as a deterministic input. The simulator can be used to simulate both a single terminal and a rail network, that is, two or more interconnected terminals. During the simulation, various statistics are gathered to assess the performance of the terminal equipment, the ITU residence time, and the terminal throughput. The simulation software has been implemented as a discrete-event simulation model, using MODSIM III as development tool. The simulator tool has been developed as part of the Platform project, funded by the Directorate General VII of the European Community.

Semantic links in integrated modelling frameworks

It is commonly accepted that modelling frameworks offer a powerful tool for modellers, researchers and decision makers, since they allow the management, re-use and integration of mathematical models from various disciplines and at different spatial and temporal scales. However, the actual re-usability of models depends on a number of factors such as the accessibility of the source code, the compatibility of different binary platforms, and often it is left to the modellers own discipline and responsibility to structure a complex model in such a way that it is decomposed in smaller re-usable sub-components. What reusable and interchangeable means is also somewhat vague; although several approaches to build modelling frameworks have been developed, little attention has been dedicated to the intrinsic re-usability of components, in particular between different modelling frameworks. In this paper, we focus on how models can be linked together to build complex integrated models. We stress that even if a model component interface is clear and reusable from a software standpoint, this is not a sufficient condition for reusing a component across different integrated modelling frameworks. This reveals the need for adding rich semantics in model interfaces.

A framework for modelling multiple resource management issues - An open modelling approach

Abstract Our experience with development and distribution of environmental decision support systems (EDSSs) for delivering research outcomes to catchment managers has identified major impediments to their adoption. These include protracted development time, focus on single impacts, difficulty in combining results with other EDSSs, and no attention to socio-economic factors. Based on the premise that decision support tools can play a major role in the integration and adoption of research outcomes, we are developing a software tool for rapid building of EDSSs which can handle multiple issues across different scales. The prototype is called the Open Modelling Engine (OME). This paper describes the background to the development of the OME, its basic architecture, an OME-built EDSS for catchment nutrient management, and concludes with a discussion on research direction and opportunity.