The issue of effectively scheduling pavement maintenance and rehabilitation treatments over a mul... more The issue of effectively scheduling pavement maintenance and rehabilitation treatments over a multi-year planning horizon plagues road authorities around the world with the significance of this issue being amplified by both an ageing pavement network and the trend towards insufficient fund allocation. The scope of the problem can be quantified as follows: if only a single treatment is able to be applied to each individual road segment in a single year, then the total number of possible programmed maintenance and rehabilitation schedule alternatives for a moderate-sized network of 1,000 road segments, with eight different treatments possible, over a twenty year anaysis period is ((1.0 × 103)8)20 = 1.0 × 10480. Assuming that a computer can build and evaluate 100 complete maintenance and rehabilitation schedules a second, to identify the optimal schedule for this 1,000 segment road network would take 3.17 × 10471 years. The overall goal of this study is to investigate the benefits of a...
The maintenance of an existing large road network is a key focus area for road authorities around... more The maintenance of an existing large road network is a key focus area for road authorities around the world. The pressures associated with the ever-increasing road network and often shrinking budgets means that it is essential that road authorities invest maintenance budgets wisely. In line with this objective, most road authorities’ employee a Pavement Management System (PMS) to assist in making maintenance decisions. PMSs must solve a very large optimization problem involving thousands of road segments with multiple possible treatments. There is a wide range in the cost of these treatments and also in the magnitude and duration of their improvement. The optimization problem is to identify a minimum cost, 20-year maintenance program that ensures all segments are maintained at an acceptable level (which varies depending on factors such as the amount of traffic and the type of traffic). In addition to the 20-year overall budget, there are yearly budgets constraints which must be met ...
The combination of local optimisation heuristics and genetic algorithms has been shown to be an e... more The combination of local optimisation heuristics and genetic algorithms has been shown to be an effective approach for finding near-optimum solutions to the Travelling Salesman Problem (TSP). In problem domains where the problem can be represented geometrically, such as networks and chemical structures, the combination of local optimisation operators and phenotype genetic operators has also been an effective approach. This paper evaluates the combination of local optimisation heuristics and phenotype genetic operators when applied to the TSP. The local optimisation heuristics reduce the search domain, while the phenotype genetic operators eliminate the creation of invalid tours and also assist the generation of sub-optimal schema. The implementation of the genetic algorithm is described and results presented.
Abstract. Considerable progress has recently been made in using clause weighting algorithms such ... more Abstract. Considerable progress has recently been made in using clause weighting algorithms such as DLM and SDF to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this improvement has been bought at the cost of extra parameters and the complexity of fine tuning these parameters to obtain optimal run-time performance. This paper examines the use of parameters, specifically in relation to DLM, to identify underlying features in clause weighting that can be used to eliminate or predict workable parameter settings. To this end we propose and empirically evaluate a simplified clause weighting algorithm that replaces the tabu list and flat moves parameter used in DLM. From this we show that our simplified clause weighting algorithm is competitive with DLM on the four categories of SAT problem for which DLM has already been optimised. 1
Thep-center problem is one of choosingp facilities froma set of candidates to satisfy the demands... more Thep-center problem is one of choosingp facilities froma set of candidates to satisfy the demands of n clients in order to minimize the maximum cost between a client and the facility towhich it is assigned. In this article, PBS, a population basedmeta-heuristic for the p-center problem, is described. PBS is a genetic algorithm basedmeta-heuristic that uses phenotype crossover and directed mutation operators to generate new starting points for a local search. For larger p-center instances, PBS is able to effectively utilize a number of computer processors. It is shown empirically that PBS has comparable performance to state-of-the-art exact and approximate algorithms for a range of p-center benchmark instances.
Abstract. To date, several types of structure for finite Constraint Satisfaction Problems have be... more Abstract. To date, several types of structure for finite Constraint Satisfaction Problems have been investigated with the goal of either improving the performance of problem solvers or allowing efficient problem solvers to be identified. Our aim is to extend the work in this area by performing a structural analysis in terms of variable connectivity for 3-SAT problems. Initially structure is defined in terms of the compactness of variable connectivity for a problem. Using an easily calculable statistic developed to measure this compactness, a test was then created for identifying 3-SAT problems as either compact, loose or unstructured (or uniform). A problem generator was constructed for generating 3-SAT problems with varying degrees of structure. Using problems from this problem generator and existing problems from SATLIB, we investigated the effects of this type of structure on satisfiability and solvability of 3-SAT problems. For the same problem length, it is demonstrated that sa...
In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum cliqu... more In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum clique problem. DLS-MC alternates between phases of iterative improvement, during which suitable vertices are added to the current clique, and plateau search, during which vertices of the current clique are swapped with vertices not contained in the current clique. The selection of vertices is solely based on vertex penalties that are dynamically adjusted during the search, and a perturbation mechanism is used to overcome search stagnation. The behaviour of DLS-MC is controlled by a single parameter, penalty delay, which controls the frequency at which vertex penalties are reduced. We show empirically that DLS-MC achieves substantial performance improvements over state-of-the-art algorithms for the maximum clique problem over a large range of the commonly used DIMACS benchmark instances. 1.
This paper presents and compares a tree-based road treatment scheduling system with the more trad... more This paper presents and compares a tree-based road treatment scheduling system with the more traditional rule-based system using a real-world road network of 1,335 road segments. The tree-based road treatment scheduling system effectively evaluates if a particular treatment should be applied in a later year instead of the current year or if an alternative ‘holding’ treatment should be applied to minimise expenditure. As a consequence, the tree-based road treatment scheduling system evaluates all feasible solutions as compared to the traditional rule-based system, which is basically a greedy search that applies rules that trigger treatments based on intervention levels in a predefined hierarchical order, which produces a single solution and does not evaluate all feasible solutions. The performance of the tree-based road treatment scheduling system was evaluated on road networks of up to 25,000 segments. For a 1,335 road segment network, the work program produced by the tree-based sys...
Abstract. Considerable progress has recently been made in using clause weight-ing algorithms to s... more Abstract. Considerable progress has recently been made in using clause weight-ing algorithms to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this im-provement has generally required extra, problem specific, parameters which have to be fine tuned to problem domains to obtain optimal run-time performance. In a previous paper, the use of parameters, specifically in relation to the DLM clause weighting algorithm, was examined to identify underlying features in clause weight-ing that could be used to eliminate or predict workable parameter settings. A sim-plified clause weighting algorithm (Maxage), based on DLM, was proposed that reduced the parameters to a single parameter. Also, in a previous paper, the struc-ture of SAT problems was investigated and a measure developed which allowed the classification of SAT problems into random, loosely structured or compactly structured. This paper extends this work by...
ABSTRACT This paper describes a real coded, parallel genetic algorithm implemented to find global... more ABSTRACT This paper describes a real coded, parallel genetic algorithm implemented to find global minimum energy structures for a two-dimensional bonded molecular model. Starting from randomly generated structures, the genetic algorithm was able to find minimum energy conformations for most structures containing between 2 and 61 atoms. The importance of tailoring genetic operators to the problem domain is demonstrated by comparing the performance of this genetic algorithm with results obtained by another genetic algorithm and other optimisation methods.
In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum cliqu... more In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum clique problem. DLS-MC alternates between phases of iterative improvement, during which suitable vertices are added to the current clique, and plateau search, during which vertices of the current clique are swapped with vertices not contained in the current clique. The selection of vertices is solely based on vertex penalties that are dynamically adjusted during the search, and a perturbation mechanism is used to overcome search stagnation. The behaviour of DLS-MC is controlled by a single parameter, penalty delay, which controls the frequency at which vertex penalties are reduced. We show empirically that DLS-MC achieves substantial performance improvements over state-of-the-art algorithms for the maximum clique problem over a large range of the commonly used DIMACS benchmark instances.
This article presents the results obtained using an unbiased Population Based Search (PBS) for op... more This article presents the results obtained using an unbiased Population Based Search (PBS) for optimizing Lennard-Jones clusters. PBS is able to repeatedly obtain all putative global minima, for Lennard-Jones clusters in the range 2 Յ N Յ 372, as reported in the Cambridge Cluster Database. The PBS algorithm incorporates and extends key techniques that have been developed in other Lennard-Jones optimization algorithms over the last decade. Of particular importance are the use of cut-and-paste operators, structure niching (using the cluster strain energy as a metric), two-phase local search, and a new operator, Directed Optimization, which extends the previous concept of directed mutation. In addition, PBS is able to operate in a parallel mode for optimizing larger clusters.
Treatment selection techniques used in Pavement Management Systems often rely on predefined prior... more Treatment selection techniques used in Pavement Management Systems often rely on predefined priorities outlined by state road agency which are subject to priority and engineering judgement. These techniques can be implemented over multi-period planning horizons however doesnt necessarily provide the best possible works program. This paper presents an overview of Pavement Management Systems, then describes and analyses the four main categories of treatment selection techniques employed within these systems. An overview of the Pavement Management System implemented by the Queensland Department of Transport and Main Roads and in particular its process of treatment selection is outlined. In addition a comparative analysis is then undertaken with each of these treatment selection categories.
The issue of effectively scheduling pavement maintenance and rehabilitation treatments over a mul... more The issue of effectively scheduling pavement maintenance and rehabilitation treatments over a multi-year planning horizon plagues road authorities around the world with the significance of this issue being amplified by both an ageing pavement network and the trend towards insufficient fund allocation. The scope of the problem can be quantified as follows: if only a single treatment is able to be applied to each individual road segment in a single year, then the total number of possible programmed maintenance and rehabilitation schedule alternatives for a moderate-sized network of 1,000 road segments, with eight different treatments possible, over a twenty year anaysis period is ((1.0 × 103)8)20 = 1.0 × 10480. Assuming that a computer can build and evaluate 100 complete maintenance and rehabilitation schedules a second, to identify the optimal schedule for this 1,000 segment road network would take 3.17 × 10471 years. The overall goal of this study is to investigate the benefits of a...
The maintenance of an existing large road network is a key focus area for road authorities around... more The maintenance of an existing large road network is a key focus area for road authorities around the world. The pressures associated with the ever-increasing road network and often shrinking budgets means that it is essential that road authorities invest maintenance budgets wisely. In line with this objective, most road authorities’ employee a Pavement Management System (PMS) to assist in making maintenance decisions. PMSs must solve a very large optimization problem involving thousands of road segments with multiple possible treatments. There is a wide range in the cost of these treatments and also in the magnitude and duration of their improvement. The optimization problem is to identify a minimum cost, 20-year maintenance program that ensures all segments are maintained at an acceptable level (which varies depending on factors such as the amount of traffic and the type of traffic). In addition to the 20-year overall budget, there are yearly budgets constraints which must be met ...
The combination of local optimisation heuristics and genetic algorithms has been shown to be an e... more The combination of local optimisation heuristics and genetic algorithms has been shown to be an effective approach for finding near-optimum solutions to the Travelling Salesman Problem (TSP). In problem domains where the problem can be represented geometrically, such as networks and chemical structures, the combination of local optimisation operators and phenotype genetic operators has also been an effective approach. This paper evaluates the combination of local optimisation heuristics and phenotype genetic operators when applied to the TSP. The local optimisation heuristics reduce the search domain, while the phenotype genetic operators eliminate the creation of invalid tours and also assist the generation of sub-optimal schema. The implementation of the genetic algorithm is described and results presented.
Abstract. Considerable progress has recently been made in using clause weighting algorithms such ... more Abstract. Considerable progress has recently been made in using clause weighting algorithms such as DLM and SDF to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this improvement has been bought at the cost of extra parameters and the complexity of fine tuning these parameters to obtain optimal run-time performance. This paper examines the use of parameters, specifically in relation to DLM, to identify underlying features in clause weighting that can be used to eliminate or predict workable parameter settings. To this end we propose and empirically evaluate a simplified clause weighting algorithm that replaces the tabu list and flat moves parameter used in DLM. From this we show that our simplified clause weighting algorithm is competitive with DLM on the four categories of SAT problem for which DLM has already been optimised. 1
Thep-center problem is one of choosingp facilities froma set of candidates to satisfy the demands... more Thep-center problem is one of choosingp facilities froma set of candidates to satisfy the demands of n clients in order to minimize the maximum cost between a client and the facility towhich it is assigned. In this article, PBS, a population basedmeta-heuristic for the p-center problem, is described. PBS is a genetic algorithm basedmeta-heuristic that uses phenotype crossover and directed mutation operators to generate new starting points for a local search. For larger p-center instances, PBS is able to effectively utilize a number of computer processors. It is shown empirically that PBS has comparable performance to state-of-the-art exact and approximate algorithms for a range of p-center benchmark instances.
Abstract. To date, several types of structure for finite Constraint Satisfaction Problems have be... more Abstract. To date, several types of structure for finite Constraint Satisfaction Problems have been investigated with the goal of either improving the performance of problem solvers or allowing efficient problem solvers to be identified. Our aim is to extend the work in this area by performing a structural analysis in terms of variable connectivity for 3-SAT problems. Initially structure is defined in terms of the compactness of variable connectivity for a problem. Using an easily calculable statistic developed to measure this compactness, a test was then created for identifying 3-SAT problems as either compact, loose or unstructured (or uniform). A problem generator was constructed for generating 3-SAT problems with varying degrees of structure. Using problems from this problem generator and existing problems from SATLIB, we investigated the effects of this type of structure on satisfiability and solvability of 3-SAT problems. For the same problem length, it is demonstrated that sa...
In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum cliqu... more In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum clique problem. DLS-MC alternates between phases of iterative improvement, during which suitable vertices are added to the current clique, and plateau search, during which vertices of the current clique are swapped with vertices not contained in the current clique. The selection of vertices is solely based on vertex penalties that are dynamically adjusted during the search, and a perturbation mechanism is used to overcome search stagnation. The behaviour of DLS-MC is controlled by a single parameter, penalty delay, which controls the frequency at which vertex penalties are reduced. We show empirically that DLS-MC achieves substantial performance improvements over state-of-the-art algorithms for the maximum clique problem over a large range of the commonly used DIMACS benchmark instances. 1.
This paper presents and compares a tree-based road treatment scheduling system with the more trad... more This paper presents and compares a tree-based road treatment scheduling system with the more traditional rule-based system using a real-world road network of 1,335 road segments. The tree-based road treatment scheduling system effectively evaluates if a particular treatment should be applied in a later year instead of the current year or if an alternative ‘holding’ treatment should be applied to minimise expenditure. As a consequence, the tree-based road treatment scheduling system evaluates all feasible solutions as compared to the traditional rule-based system, which is basically a greedy search that applies rules that trigger treatments based on intervention levels in a predefined hierarchical order, which produces a single solution and does not evaluate all feasible solutions. The performance of the tree-based road treatment scheduling system was evaluated on road networks of up to 25,000 segments. For a 1,335 road segment network, the work program produced by the tree-based sys...
Abstract. Considerable progress has recently been made in using clause weight-ing algorithms to s... more Abstract. Considerable progress has recently been made in using clause weight-ing algorithms to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this im-provement has generally required extra, problem specific, parameters which have to be fine tuned to problem domains to obtain optimal run-time performance. In a previous paper, the use of parameters, specifically in relation to the DLM clause weighting algorithm, was examined to identify underlying features in clause weight-ing that could be used to eliminate or predict workable parameter settings. A sim-plified clause weighting algorithm (Maxage), based on DLM, was proposed that reduced the parameters to a single parameter. Also, in a previous paper, the struc-ture of SAT problems was investigated and a measure developed which allowed the classification of SAT problems into random, loosely structured or compactly structured. This paper extends this work by...
ABSTRACT This paper describes a real coded, parallel genetic algorithm implemented to find global... more ABSTRACT This paper describes a real coded, parallel genetic algorithm implemented to find global minimum energy structures for a two-dimensional bonded molecular model. Starting from randomly generated structures, the genetic algorithm was able to find minimum energy conformations for most structures containing between 2 and 61 atoms. The importance of tailoring genetic operators to the problem domain is demonstrated by comparing the performance of this genetic algorithm with results obtained by another genetic algorithm and other optimisation methods.
In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum cliqu... more In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum clique problem. DLS-MC alternates between phases of iterative improvement, during which suitable vertices are added to the current clique, and plateau search, during which vertices of the current clique are swapped with vertices not contained in the current clique. The selection of vertices is solely based on vertex penalties that are dynamically adjusted during the search, and a perturbation mechanism is used to overcome search stagnation. The behaviour of DLS-MC is controlled by a single parameter, penalty delay, which controls the frequency at which vertex penalties are reduced. We show empirically that DLS-MC achieves substantial performance improvements over state-of-the-art algorithms for the maximum clique problem over a large range of the commonly used DIMACS benchmark instances.
This article presents the results obtained using an unbiased Population Based Search (PBS) for op... more This article presents the results obtained using an unbiased Population Based Search (PBS) for optimizing Lennard-Jones clusters. PBS is able to repeatedly obtain all putative global minima, for Lennard-Jones clusters in the range 2 Յ N Յ 372, as reported in the Cambridge Cluster Database. The PBS algorithm incorporates and extends key techniques that have been developed in other Lennard-Jones optimization algorithms over the last decade. Of particular importance are the use of cut-and-paste operators, structure niching (using the cluster strain energy as a metric), two-phase local search, and a new operator, Directed Optimization, which extends the previous concept of directed mutation. In addition, PBS is able to operate in a parallel mode for optimizing larger clusters.
Treatment selection techniques used in Pavement Management Systems often rely on predefined prior... more Treatment selection techniques used in Pavement Management Systems often rely on predefined priorities outlined by state road agency which are subject to priority and engineering judgement. These techniques can be implemented over multi-period planning horizons however doesnt necessarily provide the best possible works program. This paper presents an overview of Pavement Management Systems, then describes and analyses the four main categories of treatment selection techniques employed within these systems. An overview of the Pavement Management System implemented by the Queensland Department of Transport and Main Roads and in particular its process of treatment selection is outlined. In addition a comparative analysis is then undertaken with each of these treatment selection categories.
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Papers by Wayne Pullan