Abstract

This paper addresses the issue of pricing-based distributed resource allocation via scheduling in a communication network. Introducing the temporal aspect in the resource allocation problem presents new challenges e.g. in accounting for the durations and deadlines of the resource requests. Dynamic real-time pricing concepts are discussed for the decentralized sharing of network resources. A numerical example illustrates the benefit of congestion based pricing in a dynamic communication network. The quality of service that results from decentralized resource allocation is studied from the point of view of a power-controlled wireless network. The model is based on a dynamic noncooperative game and is related to recent work on centrally optimal (Pareto-optimal) distributed dynamic resource allocation. Document type: Part of book or chapter of book

Abstract

Different modelling techniques from different disciplines are needed to model complex socio-technical systems and their requirements. This paper describes the application of RESCUE, a process that integrates 4 modelling techniques to model and analyse stakeholder requirements for DMAN, a system for scheduling and managing the departure of aircraft from major European airports. It describes how human activity, use case and i* modelling were applied and integrated using synchronisation checks to model requirements on DMAN. Synchronisation checks applied at predefined stages in RESCUE revealed omissions and potential inconsistencies in the models and stakeholder requirements that, in turn, led to improvements to the models and resulting specification. The paper ends with implications for requirements model integration, and describes future work to extend and apply RESCUE. Document type: Part of book or chapter of book

Abstract

In this paper we explore tramp ship routing and scheduling. Tramp ships operate much like taxies following the available demand. Tramp operators can determine some of their demand in advance by entering into long-term contracts and then try to maximise profits from optional voyages found in the spot market. Routing and scheduling a tramp fleet to best utilise fleet capacity according to current demand is therefore an ongoing and complicated problem. Here we add further complexity to the routing and scheduling problem by incorporating voyage separation requirements that enforce a minimum time spread between some voyages. The incorporation of these separation requirements helps balance the conflicting objectives of maximising profit for the tramp operator and minimising inventory costs for the charterer, since these"br/"costs increase if similar voyages are not performed with some separation in time. We have developed a new and exact branch-and-price procedure for this problem. We use a dynamic programming algorithm to generate columns and describe a time window branching scheme used to enforce the voyage separation requirements which we relax in the master problem. Computational results show that our algorithm in general finds optimal solutions very quickly and performs much faster compared to an earlier a priori path generation method. Finally, we compare our method to an earlier adaptive large neighbourhood search heuristic and find that on similar-sized instances our approach generally uses less time to find the optimal solution than the adaptive large neighbourhood search method uses to find a heuristic solution. Document type: Book

Abstract

The realising of transport requests plays an important role for companies regarding cost. For this reason the construction of an optimal and effective transport planning and scheduling, offering the best use of transport means is hugely important. One of the researched transport problems at present is PDPTW. In this work, the PDPTW problem will be extended by adding changeable and uncertain travel times between given locations, which will then be examined and learnt by the dispatching company system. The changeable travel times are the results of traffic jams forming and propagating. The applied multi-agent approach allows us to consider the problem on the level of a whole company and on the local level analysed by a particular vehicle. The other aspects which are taken into consideration are traffic patterns, whose goal it is to facilitate the optimal routes for the given traffic patterns. These patterns contain the information about the dependencies between the traffic state on the particular routes. Document type: Part of book or chapter of book

Abstract

Part 4: Energy Efficiency International audience We study the Stochastic Traffic Engineering (STE) problem arising from the support of QoS-demanding live (e.g., real time) audio/video applications over unreliable IP-over-wireless access pipes. First, we recast the problem to be tackled in the form of a suitable nonlinear stochastic optimization problem, and then we develop a goodput analysis for the resulting IP-over-wireless pipe that points out the relative effects of fading-induced errors and congestion-induced packet’s losses. Second, we present an optimal resource-management policy that allows a joint scheduling of playin, transmit and playout rates. Salient features of the developed joint scheduling policy are that: i) it is self-adaptive; and, ii) it is able to implement reliable Constant Bit Rate (CBR) connections on the top of unreliable energy-limited wireless pipes. Document type: Part of book or chapter of book

Abstract

We present a two-part approach for verifying out-of-order execution. First, the complexity of out-of-order issue and scheduling is handled by creating an in-order abstraction of the out-of-order execution core. Second, incremental flushing addresses the complexity difficulties encountered by automated abstraction functions on very deep pipelines. We illustrate the techniques on a model of a simple out-of-order processor core. Document type: Part of book or chapter of book

Abstract

Nowadays, transport requests of the society are becoming more and more common and important. Computer systems may be a useful tool for transport companies. This paper is aimed at presenting a system which simulates the functioning of a transport company. The theoretical problem, which needs to be solved, is a dynamic Pickup and Delivery Problem with Time Windows and capacity constraints (PDPTW). The nature of the problem, its distribution and the possibility of using a lot of autonomous planning modules, predestines to apply a multi-agent approach. Multi-agent approach facilitates the introduction of elements which do not appear in classical PDPTW as company organisation, different strategies of requests acceptation by different vehicles or communication among vehicles. Document type: Part of book or chapter of book

Abstract

This paper presents a group maintenance scheduling case study for a water distribution network. This water pipeline network presents the challenge of maintaining aging pipelines with the associated increases in annual maintenance costs. The case study focuses on developing an effective pipeline replacement planning for the water utility. Replacement planning involves large capital commitment and can be difficult as it needs to balance various replacement needs under limited budgets. A Maintenance Grouping Optimization (MGO) model based on a modified genetic algorithm was utilized to develop an optimum group maintenance schedule over a 20 year cycle. An adjacent geographical distribution of pipelines was used as a grouping criterion to control the searching space of the MGO model through a Judgment Matrix. Based on the optimum group maintenance schedule, the total cost was effectively reduced compared with the schedules without grouping maintenance jobs. This optimum result can be used as a guidance to optimize the current maintenance plan for the water utility. Document type: Part of book or chapter of book

Abstract

Recently, the quality and the diversity of transport services are more and more required. Moreover, in case of a great deal of services and selling goods, a significant part of price is transport cost. Thus, the design of models and applications which make possible efficient transport planning and scheduling becomes important. A great deal of real transport problems may be modelled by using Pickup and Delivery Problem with Time Windows (PDPTW) and capacity constraints, which is based on the realization of a set of transport requests by a fleet of vehicles with given capacities. Each request is described by pickup and delivery locations, time periods when pickup and delivery operations should be performed and needed load. Application of evolutionary approach has brought good results in case of another, simpler transport problem – the Vehicle Routing Problem with Time Windows (VRPTW). This paper is aimed at proposing a straightforward extension of VRPTW based heuristics for the PDPTW. Document type: Part of book or chapter of book