An auction/sequential shortest path algorithm for the minimum cost network flow problem

Caption title.Includes bibliographical references (p. 9-10).Supported by the NSF. CCR-9103804by Dimitri P. Bertsekas

An auction algorithm for the max-flow problem

Caption title.Includes bibliographical references.Supported by the NSF. CCR-9103804by Dimitri P. Bertsekas

A faster algorithm for finding the minimum cut in a graph

"December, 1992."Includes bibliographical references (p. 25-26).Jianxiu Hao and James B. Orlin

Diagnosing infeasibilities in network flow problems

"First Draft: June 13, 1994."Includes bibliographical references (p. 20-21).by Charu C. Aggarwal

Evolutionary Decomposition of Complex Design Spaces

This dissertation investigates the support of conceptual engineering design through the decomposition of multi-dimensional search spaces into regions of high performance. Such decomposition helps the designer identify optimal design directions by the elimination of infeasible or undesirable regions within the search space. Moreover, high levels of interaction between the designer and the model increases overall domain knowledge and significantly reduces uncertainty relating to the design task at hand. The aim of the research is to develop the archetypal Cluster Oriented Genetic Algorithm (COGA) which achieves search space decomposition by using variable mutation (vmCOGA) to promote diverse search and an Adaptive Filter (AF) to extract solutions of high performance [Parmee 1996a, 1996b]. Since COGAs are primarily used to decompose design domains of unknown nature within a real-time environment, the elimination of apriori knowledge, speed and robustness are paramount. Furthermore COGA should promote the in-depth exploration of the entire search space, sampling all optima and the surrounding areas. Finally any proposed system should allow for trouble free integration within a Graphical User Interface environment. The replacement of the variable mutation strategy with a number of algorithms which increase search space sampling are investigated. Utility is then increased by incorporating a control mechanism that maintains optimal performance by adapting each algorithm throughout search by means of a feedback measure based upon population convergence. Robustness is greatly improved by modifying the Adaptive Filter through the introduction of a process that ensures more accurate modelling of the evolving population. The performance of each prospective algorithm is assessed upon a suite of two-dimensional test functions using a set of novel performance metrics. A six dimensional test function is also developed where the areas of high performance are explicitly known, thus allowing for evaluation under conditions of increased dimensionality. Further complexity is introduced by two real world models described by both continuous and discrete parameters. These relate to the design of conceptual airframes and cooling hole geometries within a gas turbine. Results are promising and indicate significant improvement over the vmCOGA in terms of all desired criteria. This further supports the utilisation of COGA as a decision support tool during the conceptual phase of design.British Aerospace plc, Warton and Rolls Royce plc, Filto

Network Flows

Not Availabl

State-of-art Multiobjective Evolutionary Algorithms-pareto Panking, Density Estimation and Dynamic Population

Electrical Engineerin

Metaheuristic approaches for Complete Network Signal Setting Design (CNSSD)

2014 - 2015In order to mitigate the urban traffic congestion and increase the travelers’ surplus, several policies can be adopted which may be applied in short or long time horizon. With regards to the short term policies, one of the most straightforward is control through traffic lights at single junction or network level. The main goal of traffic control is avoiding that incompatible approaches have green at the same time. With respect to this aim existing methodologies for Signal Setting Design (NSSD) can be divided into two classes as in following described Approach-based (or Phase-based) methods address the signal setting as a periodic scheduling problem: the cycle length, and for each approach the start and the end of the green are considered as decision variables, some binary variables (or some non-linear constraints) are included to avoid incompatible approaches having green at the same time (see for instance Improta and Cantarella, 1987). If needed the stage composition and sequence may easily be obtained from decision variables. Commercial software codes following this methodology are available for single junction control only, such Oscady Pro® (TRL, UK; Burrow, 1987). Once the green timing and scheduling have been carried out for each junction, offsets can be optimized (coordination) using the stage matrices obtained from single junction optimization (possibly together with green splits again) through one of codes mentioned below. Stage-based signal setting methods dealt with that by dividing the cycle length into stages, each one being a time interval during which some mutually compatible approaches have green. Stage composition, say which approaches have green, and sequence, say their order, can be represented through the approach-stage incidence matrix, or stage matrix for short. Once the stage matrix is given for each junction, the cycle length, the green splits and the offsets can be optimised (synchronisation) through some well established commercial software codes. Two of the most commonly used codes are: TRANSYT14® (TRL, UK) (recently TRANSYT15® has been released) and TRANSYT-7F® (FHWA, USA). Both allow to compute the green splits, the offsets and the cycle length by combining a traffic flow model and a signal setting optimiser. Both may be used for coordination (optimisation of offsets only, once green splits are known) or synchronisation. TRANSYT14® generates several (but not all) significant stage sequences to be tested but the optimal solution is not endogenously generated, while TRANSYT-7F® is able to optimise the stage sequence for each single junction starting from the ring and barrier NEMA (i.e. National Electrical Manufacturers Association) phases. Still these methods do not allow for stage matrix optimisation; moreover the effects of stage composition and sequence on network performance are not well analysed in literature... [edited by Author]XIV n.s

The multi-objective optimum design of building thermal systems

The thermal design of buildings as a multi-criterion optimisation process since there is always a pay-off (balance) to be made between capital expenditure and the operating cost of the building. This thesis investigates an approach to solving 'whole building' optimisation problems. In particular simultaneous optimisation of the plant size for a fixed arrangement of air conditioning equipment, and the control schedule for its operation to condition the space within a discrete selection of building envelopes. The optimisation is achieved by examining a combination of the cost of operating the plant, the capital cost of the plant and building construction, and maximum percentage people dissatisfied during the occupation of the building. More that one criterion is examined at a time by using multi-criteria optimisation methods. Therefore rather than a single optimum, a payoff between the solutions is sort. The benefit of this is that it provides a more detailed information about the characteristics of the problem and more design solutions available to the end user. The optimisation is achieved using a modified genetic algorithm using Pareto ranking selection to provide the multi-criterion fitness selection. Specific methods for handling the high number of constraints within the problem are examined. A specific operator is designed and demonstrated to deal with the discontinuous effects of the three separate seasons, which are used for the plant selection and for the three separate control schedules. Conclusions are made with respect to the specific application of the multi-criterion optimisation to, building services systems, their control, and the viability of 'whole building design' optimisation