Multiple Scenario Approach Research Articles

Dynamic arc routing problem in road maintenance service with uncertain travel and service times

This paper describes a dynamic arc routing problem motivated by daily maintenance operations on road networks to improve the maintenance efficiency. Uncertain service and travel times on road segments are considered and defined using discrete stochastic distribution. An algorithm based on the multiple scenario approach (MSA) is developed to deal with the uncertainty of the network. The MSA scheme is triggered to update the maintenance routing by an event-driven mechanism. The computational experiments demonstrate the effectiveness of the algorithm.

Predicting Salinization Trends in a Lowland Coastal Aquifer: Comacchio (Italy)

The coastal aquifer salinization is an urgent problem caused by groundwater resources overexploitation and climate change. This phenomenon is enhanced in areas lying below the sea level, like the polders in the Netherlands or the Po River lowland in Italy. In these reclaimed lands the saltwater intrusion is usually controlled by a network of irrigation canals that supplies freshwater to the shallow aquifer, maintaining soil salinity at acceptable levels. The 2012 was dramatic in terms of agricultural water supply, since the Po River plain experienced a prolonged drought. Despite this, continuous monitoring of piezometric heads and total dissolved solids (TDS) near a canal (Canale della Gronda) demonstrated that freshening was occurring in the shallow portion (first 4 m) of the unconfined aquifer, while the bottom part was characterized by elevated relic salinity. The two-dimensional model SEAWAT was calibrated using piezometric heads and TDS depth profiles measured along a transect perpendicular to the canal. The calibrated model was then used to predict the behaviour of this cross section using a multiple scenario approach: increase in evapotranspiration induced by temperature increase; increase in the frequency of extreme high rainfall events; extreme drought conditions; and canal dewatering due to salinization of the water courses. Moreover, for each scenario, two sub-scenarios were run to account for projected sea level rise. The first three scenarios had only a minor influence on the aquifer salinization rate, while the fourth one predicted serious upward flux of the high salinity groundwater actually residing in the bottom of the unconfined aquifer. The scenarios quantified the possible future effects on groundwater salinization and could be useful to find adaptation strategies to manage the water resources of this and similar areas.

Spatially explicit reconstruction of past land cover from pollen records using a multiple scenario approach

Spatially explicit reconstruction of past land cover from pollen records using a multiple scenario approach

Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports

The problem of transporting patients or elderly people has been widely studied in literature and is usually modeled as a dial-a-ride problem (DARP). In this paper we analyze the corresponding problem arising in the daily operation of the Austrian Red Cross. This nongovernmental organization is the largest organization performing patient transportation in Austria. The aim is to design vehicle routes to serve partially dynamic transportation requests using a fixed vehicle fleet. Each request requires transportation from a patient's home location to a hospital (outbound request) or back home from the hospital (inbound request). Some of these requests are known in advance. Some requests are dynamic in the sense that they appear during the day without any prior information. Finally, some inbound requests are stochastic. More precisely, with a certain probability each outbound request causes a corresponding inbound request on the same day. Some stochastic information about these return transports is available from historical data. The purpose of this study is to investigate, whether using this information in designing the routes has a significant positive effect on the solution quality. The problem is modeled as a dynamic stochastic dial-a-ride problem with expected return transports. We propose four different modifications of metaheuristic solution approaches for this problem. In detail, we test dynamic versions of variable neighborhood search (VNS) and stochastic VNS (S-VNS) as well as modified versions of the multiple plan approach (MPA) and the multiple scenario approach (MSA). Tests are performed using 12 sets of test instances based on a real road network. Various demand scenarios are generated based on the available real data. Results show that using the stochastic information on return transports leads to average improvements of around 15%. Moreover, improvements of up to 41% can be achieved for some test instances.

Will Energy Infrastructure Systems in Germany Be More Decentralized in the Future? A Participatory Scenario Process

Decentralized power generation is gaining significance in liberalized electricity markets. This paper explores the future development of the German energy infrastructure systems with regard to decentralization. Four scenarios have been developed using a participatory multiple-scenario approach. Stakeholders involved in production, consumption, and governance were involved. The results of the study show that the key factor driving the future decentralization of the energy infrastructure system is not technological development. In fact, the economic and political boundary conditions are decisive. It is shown that a scenario-based approach provides substantiated insights into the energy future. The methodology employed is presented, followed by a detailed description of each of the four scenarios. The developed scenarios differ in the share of decentralized energy supply and therefore both structurally and technologically. Based on the historic development, it is analysed whether the trends and developments of the four scenarios are already becoming apparent today.

Equifinality and uncertainty in the interpretation of pollen data: the Multiple Scenario Approach to reconstruction of past vegetation mosaics

The long-term goal of pollen analysis has always been the reconstruction of past vegetation mosaics. However, the pollen signal is spatially integrated, and ecologically distinct vegetation structures can produce identical pollen signals. This paper proposes an iterative approach to reconstruction, the Multiple Scenario Approach, which involves creating a large number of hypothetical landscapes using a combination of deterministic and probabilistic `rules' for plant placement coupled with environmental parameters such as topography, simulating the pollen assemblage produced by each, and comparing them statistically with a sedimentary pollen signal to identify possible reconstructions. The method expressly aims to find multiple possible reconstructions, and also gives some insight into the spatial aspects of the vegetation being reconstructed in addition to its composition.

Using models of pollen dispersal and deposition in hilly landscapes: Some possible approaches

Recent developments in the modelling of pollen dispersal and deposition have led to the development of user-friendly computer software for simulating vegetation mosaics and pollen assemblages at specified points within those mosaics. In this paper we discuss the possible application of these approaches to modelling the pollen deposition in mountain areas. First, we demonstrate the use of the Multiple Scenario Approach by reconstructing mid-Holocene tree line position in the southern Dark Peak area of the Peak District in northern England from a published pollen record. However, the underlying model of pollen dispersal and deposition assumes a flat landscape, which makes extending the approach to mountainous areas problematic. Therefore we also present simulation experiments exploring the effects of modifying aspects of the existing model to better simulate the montane situation (ecotone structure, changes in the wind rose to mimic the effects of topography on aerial pollen transport). We suggest that, as a first approximation, topographic effects can be incorporated in the models by varying the wind rose at the sampling point to reflect the impact of topography on air flow.

Scenario-Based Planning for Partially Dynamic Vehicle Routing with Stochastic Customers

The multiple vehicle routing problem with time windows (VRPTW) is a hard and extensively studied combinatorial optimization problem. This paper considers a dynamic VRPTW with stochastic customers, where the goal is to maximize the number of serviced customers. It presents a multiple scenario approach (MSA) that continuously generates routing plans for scenarios including known and future requests. Decisions during execution use a distinguished plan chosen, at each decision, by a consensus function. The approach was evaluated on vehicle routing problems adapted from the Solomon benchmarks with a degree of dynamism varying between 30% and 80%. They indicate that MSA exhibits dramatic improvements over approaches not exploiting stochastic information, that the use of consensus function improves the quality of the solutions significantly, and that the benefits of MSA increase with the (effective) degree of dynamism.

A Reappraisal of Energy Supply and Demand in 2050

In this paper dealing with the medium term (2020) and long term (2050) world energy mix the author has attempted to present a single most likely scenario, contrary to the usual multiple scenario approach. A second main characteristic is that the emphasis is not on the uncertainties of energy demand but on the potential limitations on the offer of fossil fuels and mainly of oil and gas. The main conclusions are that by 2050 we will need a large increase of the world nuclear industry, not only for the production of electricity but also to complement the oil industry, by providing it with necessary CO2 emissions freeheat and hydrogen. This nuclear- based hydrogen would allow to give a sustainable future to the oil industry, and to the automobile industry, by providing synthesis fuels on an economically and ecologically sound basis.

Multiple scenario development: Its conceptual and behavioral foundation

AbstractThis paper examines the multiple scenario approach as an important corporate innovation in strategic planning. Using a participant/observer perspective, I examine how scenario planning tries to meet certain methodological, organizational and psychological challenges facing today's senior managers. Three prime characteristics are identified as setting the scenario approach apart from more traditional planning tools: (1) the script or narrative approach, (2) uncertainty across rather than within models, and (3) the decomposition of a complex future into discrete states. After exploring the intellectual roots of scenario planning, I examine such organizational aspects as the need for diversity of views and the importance of simplicity and manageability. Both benefits and obstacles to using scenarios in organizations are identified. Cognitive biases are examined as well, especially the well‐known biases of overconfidence and the conjunction fallacy. Two experiments test the impact of scenarios on people's subjective confidence ranges. Another two experiments test the internal coherence of subjects' beliefs. The psychological benefit of scenario planning appears to tie in the exploitation of one set of biases (e.g., conjunction fallacies) to counteract another (such as overconfidence).

Not forecasts but multiple scenarios when coping with uncertainties in the competitive environment

The paper discusses the advantages and disadvantages of the multiple scenario approach in relation to traditional strategic planning in a turbulent environment. It describes the procedures developed at the Turku School of Economics and discusses the results of a survey to explore the differences between companies which do and do not use scenarios.

Multiple scenario approach and strategic behaviour in European companies

AbstractNowadays, scenarios are a popular subject in management literature. However, information available about how extensively scenarios are used and the possible motives for their use, as well as their effects on strategic behaviour in companies, has hitherto been very limited. Results of a survey among Fortune's top 1000 companies in the U.S.A. in 1977 and 1981 showed a growing corporate interest in scenarios. A survey of the use of scenarios in large Western European companies in 1981 provided evidence of similar interest in Europe. In this article, results of the European survey are presented and the differences between user and non‐user attitudes towards the future among European firms analysed and the implications for strategic behaviour outlined.

Using Multiple Scenarios for Strategic Environmental Assessment: Implications for Marketing Management

In this article, we present empirical results that document the critical changes in planning attitudes and practices and their implications on strategic market planning. The particular focus of this article is to illustrate the growing use of multiple scenarios as an approach to strategic environmental assessment, and to present key factors that marketing management must consider when adopting the multiple scenario approach.

The United States Coast Guard Computer‐Assisted Search Planning system (CASP)

AbstractThis paper provides an overview of the Computer‐Assisted Search Planning (CASP) system developed for the United States Coast Guard. The CASP information processing methodology is based upon Monte Carlo simulation to obtain an initial probability distribution for target location and to update this distribution to account for drift due to currents and winds. A multiple scenario approach is employed to generate the initial probability distribution. Bayesian updating is used to reflect negative information obtained from unsuccessful search. The principal output of the CASP system is a sequence of probability “maps” which display the current target location probability distributions throughout the time period of interest. CASP also provides guidance for allocating search effort based upon optimal search theory.