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Traditionally, in the Netherlands, the procurement procedure for infrastructure does not start until the public decision-making procedure is fully completed. In the new procurement strategy, early contractor involvement is applied by carrying out the procurement procedure and the public planning procedure simultaneously. This article explores the first experiences and lessons learned with early contractor involvement in four Dutch infrastructure projects. It can be concluded that the new strategy adds value in terms of time gains, improved project control and more innovative solutions. However, to optimize early contractor involvement, the differences between the competitive procurement procedures and the open, cooperative public planning procedures need to be bridged.

Currently, the European air transport system is experiencing an annual growth of 7%. With an increasing number of flights, airports are reaching their capacity limits and are becoming a bottleneck in the system. Mantea is a European Commission funded project dealing with this issue. This paper focuses on planning decision support tools for airport traffic controllers.

The objective of our planning tools is to achieve a better use of the available airport infrastructure (taxiways and runways). To generate a safe plan, many rules must be taken into account that restrict the usage of airport tarmac: international regulations, airport operational procedures, aircraft performance, weather conditions and sometimes even controller “usual practices”. To generate a realistic plan, extensive monitoring of the traffic situation as well as suitable timing must be achieved. In the life cycle of a flight, 11 out of 15 possible causes of delay occur in an interval of 10-20 minutes, between aircraft start-up request and push-back. This means that precise planning before the end of this period is highly improbable. On the other hand, planning after this period implies the need for fast responses from the system.

In the Mantea project, an architecture is proposed in which a co-operative approach is taken towards planning aircraft movements at the airport. Controllers will be supported by planning tools that help assigning routes and departure times to controlled vehicles, in planning runway allocation (departure sequence) and occupancies, and in monitoring plan progress during flight phases. The planning horizon relates to medium term operations, i.e. 2-20 minutes ahead. The Mantea planning tools implement the following functions: runway departure planning, routing, and plan conformance monitoring. The tools will reduce the controller's workload, increase the level of safety for airport surface movements, and reduce the number of delays and operating costs for the airliners.

In this paper, we will focus on the constraint satisfaction programming techniques used in Mantea for (1) runway departure planning, (2) itinerary search and taxi planning functions. The airport tarmac and runway vicinity air routes have been modelled as a graph. Real time constraints have brought us to develop an algorithm linear in complexity for the itinerary search problem. Operational pressure has led us to develop fast search strategies for scheduling (i.e. use of heuristics, hill climbing…).

Continual rising fuel costs and rapidly increasing vehicle costs have generated management awareness of the costs incurred in physical distribution. Inevitably, management attention on the distribution function is drawn towards potential cost savings and increases in efficiency. Where transport costs represent a significant part of the total distibution costs, then one area which determines the efficiency of all others is the vehicle routing and scheduling activity which could collectively be known as load planning.

The main objective of this paper is to introduce the development of a novel feature recognition system for escape route planning. The genetic algorithm (GA) can be a useful tool in solving route planning problems.

A computer‐aided design (CAD) system is proposed to help to predict the best escape route. The system is based on a feature recognition process, which will scan a CAD drawing to determine the centroid points of corridors, and determine the best escape route with the help of GA.

The feature recognition system provides a quick method of determining the available pathways for use in escape route planning.

Factors such as multiple story buildings, number of occupants, or fire spread are not considered. Thus the system will be useful in the initial stages of escape route planning.

The system is limited to perpendicular walls, which should be of the same thickness. Doorways should also be a constant size. Thus the system will be useful in determining where escape routes exist, and attempt to determine the best route based on that information.

This paper shows how legacy drawings from various CAD systems may be reused to plan escape routes, rather than creating new drawings for the same purpose. This is useful to those in escape route planning, since the redrawing of plans using custom software is inefficient.

This paper aims to present a comprehensive review in major research areas of unmanned air vehicles (UAVs) navigation, i.e. three degree-of-freedom (3D) path planning, routing algorithm and routing protocols. The paper is further aimed to provide a meaningful comparison among these algorithms and methods and also intend to find the best ones for a particular application.

The major UAV navigation research areas are further classified into different categories based on methods and models. Each category is discussed in detail with updated research work done in that very domain. Performance evaluation criteria are defined separately for each category. Based on these criteria and research challenges, research questions are also proposed in this work and answered in discussion according to the presented literature review.

The research has found that conventional and node-based algorithms are a popular choice for path planning. Similarly, the graph-based methods are preferred for route planning and hybrid routing protocols are proved better in providing performance. The research has also found promising areas for future research directions, i.e. critical link method for UAV path planning and queuing theory as a routing algorithm for large UAV networks.

The proposed work is a first attempt to provide a comprehensive study on all research aspects of UAV navigation. In addition, a comparison of these methods, algorithms and techniques based on standard performance criteria is also presented the very first time.

The purpose of this study is to provide an alternative graph-based airspace model for more effective free-route flight planning.

Based on graph theory and available data sets describing airspace, as well as weather phenomena, a new FRA model is proposed. The model is applied for near to optimal flight route finding. The software tool developed during the study and complexity analysis proved the applicability and timed effectivity of the flight planning approach.

The sparse bidirectional graph with edges connecting only (geographically) closest neighbours can naturally model local airspace and weather phenomena. It can be naturally applied to effective near to optimal flight route planning.

Practical results were acquired for one country airspace model.

More efficient and applicable flight planning methodology was introduced.

Aircraft following the new routes will fly shorter trajectories, which positively influence on the natural environment, flight time and fuel consumption.

The airspace model proposed is based on standard mathematical backgrounds. However, it includes the original airspace and weather mapping idea, as well as it enables to shorten flight planning computations.

The purpose of this paper is to present the design and evaluation of an integrated system that supports planners and dispatchers to deliver enhanced courier operations. In addition to regular deliveries and pickups, these operations include: first, mass deliveries to be served over a horizon of multiple days; and second, real-time dynamic requests (DRs) to be served within the same service period.

To address the aforementioned challenges, the authors developed an architecture that enhances a typical fleet management system by integrating purpose designed methods. Specifically, the authors plan mass deliveries taking into account typical routes of everyday operations. For planning DRs in real time, the authors propose an efficient insertion heuristic.

The results from testing the proposed optimization algorithms for planning mass deliveries and real-time DRs are encouraging, since the proposed algorithms outperform current practices. Testing in a practical courier environment, indicated that the enhanced planning system may improve significantly operational performance.

The proposed optimization algorithm for the dynamic aspect of this problem comprises a heuristic approach that reaches suboptimal solutions of high quality. The development of fast optimal algorithms for solving these very interesting and practical problems is a promising area for further research.

The proposed integrated system addresses significant problems of hybrid courier operations in an integrated, balanced manner. The tests showed that the allocation of flexible orders within a three-day time horizon improved the cost per flexible order by 7.4 percent, while computerized routing improved the cost of initial (static) routing by 14 percent. Furthermore, the proposed method for managing DRs reduced the excess cost per served request by over 40 percent. Overall, the proposed integrated system improved the total routing costs by 16.5 percent on average compared to current practices.

Both the planning problems and the related solution heuristics address original aspects of practical courier operations. Furthermore, the system integration and the proposed systematic planning contribute to the originality of the work.

The ocean transportation of automobiles is carried out by specialized Roll‐on/Roll‐off ships, which are designed to carry a large number of automobiles at a time. Many of these shipping companies have vertically integrated or collaborated with other logistics services providers to offer integrated maritime logistics solution to car manufacturers. The purpose of this study is to develop an optimization model to address the tactical level maritime logistics planning for such a company.

The problem is formulated as a mixed integer linear program and we propose an iterative combined Ant colony and linear programming‐based solution technique for the same.

This paper can integrate the maritime transportation planning of internally managed cargoes with the inventory management at the loading and discharging ports to minimize supply‐chain cost and also maximize additional revenue through optional cargoes using same fleet of ships.

The mathematical model does not consider the variability in production and consumption of products across various locations, travel times between different nodes, etc.

The suggested mathematical model to the supply‐chain planning problem and solution technique can be considered in the development of decision support system for operations planning.

This paper extends the maritime inventory routing model by considering simultaneous planning of optional cargoes with internally managed cargoes.

To provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics.

Joint route planning is a measure that companies can take to decrease the costs of their distribution activities. Essentially, this can either be achieved through horizontal cooperation or through outsourcing distribution to a logistics service provider. The synergy value is defined as the difference between distribution costs in the original situation where all entities perform their orders individually, and the costs of a system where all orders are collected and route schemes are set up simultaneously to exploit economies of scale. This paper provides estimates of synergy values, both in a constructed benchmark case and in a number of real‐world cases.

It turns out that synergy values of 30 per cent are achievable. Furthermore, intuition is developed on how the synergy values depend on characteristics of the distribution problem under consideration.

The developed intuition on the nature of synergy values can help practitioners to find suitable combinations of distribution systems, since synergy values can quickly be assessed based on the characteristics of the distribution problem, without solving large and difficult vehicle routing problems.

This paper addresses a major impediment to horizontal cooperation: estimating operational savings upfront.