A new focus on risk reduction: An ad hoc decision support system for humanitarian relief logistics

Particularly in the early phases of a disaster, logistical decisions are needed to be made quickly and under high pressure for the decision‐makers, knowing that their decisions may have direct consequences on the affected society and all future decisions. Proactive risk reduction may be helpful in providing decision‐makers with optimal strategies in advance. However, disasters are characterized by severe uncertainty and complexity, limited knowledge about the causes of the disaster, and continuous change of the situation in unpredicted ways. Following these assumptions, we believe that adequate proactive risk reduction measures are not practical. We propose strengthening the focus on ad hoc decision support to capture information in almost real time and to process information efficiently to reveal uncertainties that had not been previously predicted. Therefore, we present an ad hoc decision support system that uses scenario techniques to capture uncertainty by future developments of a situation and an optimization model to compute promising decision options. By combining these aspects in a dynamic manner and integrating new information continuously, it can be ensured that a decision is always based on the best currently available and processed information. And finally, to identify a robust decision option that is provided as a decision recommendation to the decision‐makers, methods of multi‐attribute decision making (MADM) are applied. Our approach is illustrated for a facility location decision problem arising in humanitarian relief logistics where the objective is to identify robust locations for tent hospitals to serve injured people in the immediate aftermath of the Haiti Earthquake 2010.Frank Schätter, Marcus Wiens and Frank Schultman

Projektplanungsmodelle und -methoden für den Rückbau von Bauwerken

Vor dem Hintergrund einer sich verschärfenden Umweltgesetzgebung sowie der Erkenntnis, dass Bauabfälle sich grundsätzlich für eine Stoffkreislaufführung eignen, hat der Rückbau von Bauwerken in den letzten Jahren verstärkt an Bedeutung gewonnen. Aufgrund oftmals strenger Zeit- und Kostenvorgaben für einen Rückbau, begrenzter Verfügbarkeit von Personal und Betriebsmitteln, einer weitgehenden Unikatfertigung sowie wechselnder Standorte kommt dabei der projektorientierten Planung von Maßnahmen auf der Baustelle große Bedeutung zu. Im Rahmen des Beitrages werden Ansätze zur Modellierung und Lösung der sich hieraus ergebenden Probleme zur Planung und Optimierung von (Rück-) Bauabläufen unter Verwendung von Projektplanungsmodellen und -methoden vorgestellt. Hierbei werden neben betriebswirtschaftlichen auch umweltrelevante sowie technische Fragestellungen im Zusammenhang mit der Planung von Rückbauprojekten aufgegriffen. Eine Anwendung der Planungsansätze auf reale Gebäude zeigt, dass sich durch Kombination von Gebäuderückbau und Aufbereitungstechnik eine Qualitätsverbesserung von Recyclingbaustoffen erzielen lässt. Zur Umsetzung der hierzu erforderlichen Maßnahmen werden unter Berücksichtigung individueller abfallwirtschaftlicher Rahmenbedingungen der jeweiligen Planungsregion, gebäude- und baustellenbezogener Besonderheiten, technischer sowie kapazitiver Restriktionen Ablaufpläne für den Gebäuderückbau berechnet. Die für unterschiedliche Planungsregionen vorgenommenen Modellrechnungen weisen nach, dass sich die Demontage von Gebäuden gegenüber einem konventionellen Gebäudeabbruch unter bestimmten Rahmenbedingungen bereits wirtschaftlich vorteilhaft realisieren lässt. Abgerundet wird der Beitrag durch einen Ausblick auf Möglichkeiten einer Realisierung komplexer Bauabläufe auch unter strengen Zeitvorgaben sowie bei begrenzten Platzverhältnissen mit Hilfe fertigungssynchroner Ressourceneinsatzplanung sowie auf die Berücksichtigung von Unsicherheiten in der Planung und Ausführung von Rückbauprojekten

What information is necessary to assess the environmental impacts of deconstruction?

4D modeling - the simulation and visualisation of the construction process - is now a common method used during the building construction process with reasonable support from existing software. The goal of this paper is to examine the information needs required to model the deconstruction/demolition process of a building. The motivation is the need to reduce the impacts on the local environment during the deconstruction process. The focus is on the definition and description of the activities to remove building components and on the assessment of the noise, dust and vibration implications of these activities on the surrounding environment. The outcomes of the research are: i. requirements specification for BIM models to support operational deconstruction process planning, ii. algorithms for augmenting the BIM with the derived information necessary to automate planning of the deconstruction process with respect to impacts on the surrounding environment, iii. algorithms to build naive deconstruction activity schedules

Secondary raw material markets in the C&D sector: Study on user acceptance in southwest Germany

In industrialized countries, regulations demand increasingly higher recycling (RC) rates and many efforts are undertaken to recycle construction and demolition (C&D) waste fractions. The C&D sector has indisputable relevance due to the highest mineral waste fraction, high numbers of employees and turnovers. High-quality RC construction products can be produced to substitute primary resources and reduce land use. This empirical study analyses the acceptance of RC materials in Germany particularly of private awarding authorities in their private construction project(s). In 41 structured interviews, data is collected and evaluated based on hypotheses. Qualitative and quantitative analyses show that acceptance problems cannot be stated. How-ever, medium knowledge and low experience with RC construction materials as well as communication problems are identified. The respondents have no concerns and tend to trust in RC construction materials, but this is decreasing with the increased structural importance of the materials. Surprisingly, quality is the most frequently mentioned decision criteria in private construction projects, followed by cost. Private awarding authorities see no increase of their property value by using RC construction materials. And, the majority is unwilling to pay a premium for RC construction materials. Higher material quality standards, regular government reviews and financial support are seen conducive

On the integration of diverging material flows into resource‐constrained project scheduling

This study deals with an extension of the resource-constrained project scheduling problem (RCPSP) by constraints on material flows released during the execution of project activities. These constraints arise from limited processing capacities for materials and maximum inventories of intermediate storage facilities. Production scheduling problems with converging material flows have been studied extensively. However, this is the first project scheduling problem integrating diverging material flows typically observed in dismantling projects, e.g., building deconstruction, power plant decommissioning, or battery/car decommissioning. Diverging material flows do not directly impact the project planning but only impose delays in the case of congestion. We model material flows by using operations that represent the processing of materials, and cumulative resources that represent storage facilities. As a method for efficiently generating starting solutions, we propose a schedule generation scheme tailored to the particular precedence structure of such problems. Furthermore, we extensively study the schedule generation scheme’s performance on generated test instances and compare it to the constraint programming solver IBM ILOG CP Optimizer. It turns out that the solution quality strongly depends on the employed model and that neither of the two solution methods is generally superior

Instance dataset for resource-constrained project scheduling with diverging material flows

This data article describes an instance dataset motivated by the problem of scheduling a project with diverging material flows. Such material flows are released during the execution of the project and are subject to limited processing and storage capacities. Typical examples are nuclear dismantling or other deconstruction/demolition projects, where large amounts of material must be classified, scanned for hazardousness, and processed accordingly. The problem setting is mathematically described as a resource-constrained project scheduling problem with cumulative resources (RCPSP/c). The RCPSP/c deals with finding a project schedule with minimal makespan that satisfies temporal, renewable resource, and cumulative resource constraints. In total, the dataset comprises 192 artificially generated instances that are suitable for testing models and solution methods. In addition, we provide our best found solution for each instance and different modeling variants (e.g., for two types of objective functions). These solutions were computed by heuristic solution methods. The dataset serves as a benchmark for researchers evaluating the performance of solution methods for the RCPSP/c or the more general problem class with resources that can be produced and consumed