Mark G. Wallace

Monash University (Australia) · Faculty of Information Technology

Designing the layout of a chemical plant is a complex and important task. Its main objective is to find a most economical spatial arrangement of the equipment and associated pipes that satisfies construction, operation, maintenance and safety constraints. The problem is so complex it is still solved manually, taking multiple engineers many months (...

Stochastic programming is concerned with decision making under uncertainty, seeking an optimal policy with respect to a set of possible future scenarios. This paper looks at multistage decision problems where the uncertainty is revealed over time. First, decisions are made with respect to all possible future scenarios. Secondly, after observing the...

Optimizing the layout of the equipment and connecting pipes that form a chemical plant is an important problem, where the aim is to minimize the total cost of the plant while ensuring its safety and correct operation. The complexity of this problem is such that it is still solved manually, taking multiple engineers several years to complete. Most r...

Combinatorial optimisation problems often contain uncertainty that has to be taken into account to produce realistic solutions. This uncertainty is usually captured in scenarios, which describe different potential sets of problem parameters based on random distributions or historical data. While efficient algorithmic techniques exist for specific p...

Constraint programming allows difficult combinatorial problems to be modelled declaratively and solved automatically. Advances in solver technologies over recent years have allowed the successful use of constraint programming in many application areas. However, when a particular solver's search for a solution takes too long, the complexity of the c...

Using a health impact assessment framework, we estimated the population health effects arising from alternative land-use and transport policy initiatives in six cities. Land-use changes were modelled to reflect a compact city in which land-use density and diversity were increased and distances to public transport were reduced to produce low motoris...

Constraint Programming (CP) standardizes many specialized “global constraints” allowing high-level modelling of combinatorial optimization and feasibility problems. Current Mixed-Integer Linear Programming (MIP) technology lacks both a modelling language and a solving mechanism based on high-level constraints. MiniZinc is a solver-independent CP mo...

The problem addressed in this paper, of routing and scheduling freight trains within a scheduled passenger rail network, prevails in many large countries. The actual departure and arrival times of freight trains are not important, and nor are their routes. Only a starting station and destination station are specified on the day of travel. The curre...

The symmetries that appear in many constraint problems can be used to significantly speed up the search for solutions to these problems. While the accurate detection of symmetries in instances of a given constraint problem is possible, current methods tend to be impractical for real-sized instances. On the other hand, methods capable of detecting p...

In industrial transportation, the forecast demand at each destination may be affected by a number of factors. Consequently, a conventional transport plan often fails to match the reality, and the planned transport capacity is either insufficient to meet the demand or wastefully excessive. In this paper, we introduce a new algorithm to generate a mi...

Boolean satisfiability solving is a powerful approach for testing the feasibility of propositional logic formulae in conjunctive normal form. Nowadays, Boolean satisfiability solvers efficiently handle problems with millions of clauses and hundreds of thousands of Boolean variables. But still many combinatorial problems such as resource-constrained...

An important variant of the resource-constrained project scheduling problem is to maximise the net present value. Significant progress has been made recently on this problem for both exact and inexact methods. The lazy clause generation based constraint programming approach is the state of the art among the exact methods and is briefly discussed. T...

We consider a project scheduling problem where a number of tasks need to be scheduled. The tasks share resources, satisfy precedences, and all tasks must be completed by a common deadline. Each task is associated with a cash flow (positive or negative value) from which a “net present value” is computed dependent upon its completion time. The object...

In this study, we investigate a hybrid Lagrangian relaxation ant colony optimisation for optimisation version of the car sequencing problem. Several cars are required to be scheduled on an assembly line and each car requires a number of options such as sunroof and/or air conditioning. These cars are required to be sequenced such that sub-sequences...

Option types are a powerful abstraction that allows the concise modelling of combinatorial problems where some decisions are relevant only if other decisions are made. They have a wide variety of uses: for example in modelling optional tasks in scheduling, or exceptions to a usual rule. Option types represent objects which may or may not exist in t...

Technology for combinatorial optimization is rapidly changing, and as the size and scope of problems that can be solved steadily increases, the complexity of the underlying technology is growing. We foresee a huge demand for both the simplification of use of combinatorial optimization technology (so called "model and run" capabilities), as well as...

Drawings of highly connected (dense) graphs can be very difficult to read. Power Graph Analysis offers an alternate way to draw a graph in which sets of nodes with common neighbours are shown grouped into modules. An edge connected to the module then implies a connection to each member of the module. Thus, the entire graph may be represented with m...

We present a generic exact method for minimizing the project duration of the resource-constrained project scheduling problem with generalized precedence relations (Rcpsp/max). This is a very general scheduling model with applications areas such as project management and production planning. Our method uses lazy clause generation, i.e., a hybrid of...

Despite of the practicality of the motivation of the inventory routing problem (IRP), there are few successful implementation stories of IRP based decision support systems which utilize optimization algorithms. Besides the fact that the IRP is an extremely ...

For most airlines, there are numerous policies, agreements and regulations that govern the workload of airline crew. Although some constraints are formally documented, there are many others based on established practice and tacit understanding. Consequently, the task of developing a formal representation of the constraints that govern the working c...

The Resource-constrained Project Scheduling Problem (Rcpsp), in which a schedule must obey resource constraints and precedence constraints between pairs of activities, is one of the most studied scheduling problems. An important variation of this problem (RcpspDc) is to find a schedule which maximises the net present value (discounted cash flow). L...

In a suburban passenger railway network, a delay of a single train is likely to affect not only the passengers aboard or waiting for that train, but those on subsequent trains as well. These knock-on effects are caused by the delayed train blocking sections of track and lead to congestion and slower boarding rate on overcrowded trains. When a delay...

The Resource-constrained Project Scheduling Problem (Rcpsp), in which a schedule must obey the resource constraints and the precedence constraints between pairs of activities, is one of the most studied scheduling problems. An important variation of the problem (RcpspDc) is to find a schedule which maximises the net present value (discounted cash f...

Symmetry breaking is the process of eliminat-ing redundant search by taking advantage of the symmetries in a problem. Symmetry break-ing techniques can be combined with other search heuristics, such as branching constraints and variable orderings. The interaction be-tween dynamic symmetry breaking and domain splitting is discussed, and preliminary...

This paper is the second of two papers entitled “Airline Planning Benchmark Problems”, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. The former has, to date, been under-represented in the optimisation literature, due in part to the diff...

This paper is the first of two papers entitled “Airline Planning Benchmark Problems”, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. While optimisation has made an enormous contribution to airline planning in general, the area suffers fr...

Existing ship scheduling approaches either ignore constraints on ship draft (distance between the waterline and the keel), or model these in very simple ways, such as a constant draft limit that does not change with time. However, in most ports the draft restriction changes over time due to variation in en-vironmental conditions. More accurate cons...

The G12 project is developing a software environment for stating and solving combinatorial problems by mapping a high-level model of the problem to an efficient combination of solving methods. Model annotations are used to control this process. In this paper we explain the mapping to branch-and-price solving. Dantzig-Wolfe decomposition is automati...

The global cumulative constraint was proposed for modelling cumulative resources in scheduling problems for finite domain (FD) propagation. Since that time a great deal of research has investigated new stronger and faster filtering techniques for cumulative, but still most of these techniques only pay off in limited cases or are not scalable. Recen...

The presence of symmetries in a constraint satisfaction prob-lem gives an opportunity for more efficient search. Within the class of matrix models, we show that the problem of deciding whether some well known permutations are model symmetries (solution symmetries on every instance) is undecidable. We then provide a new approach to prov-ing the mode...

The technical report presents a generic exact solution approach for minimizing the project duration of the resource-constrained project scheduling problem with generalized precedences (Rcpsp/max). The approach uses lazy clause generation, i.e., a hybrid of finite domain and Boolean satisfiability solving, in order to apply nogood learning and confl...

This paper presents Constraint Programming as a natural formalism for modelling problems, and as a flexible platform for solving them. CP has a range of techniques for handling constraints including several forms of propagation and tailored algorithms for global constraints. It also allows linear programming to be combined with propagation and nove...

Automatic symmetry detection has received a significant amount of interest, which has resulted in a large number of proposed methods. This paper reports on our experiences while implementing the approach of J. F. Puget [Lect. Notes Comput. Sci. 3709, 475–489 (2005; Zbl 1153.68477)]. In particular, it proposes a modification to the approach to deal...

Routing vehicles to serve customers is a problem that naturally arises in many distribution systems. Moreover, fleet management requires fast algorithms able to cope with continuously changing needs. Many efforts have been addressed to tackle different vehicle routing problem's variants. Among them, the pick up and delivery problem with time window...

The global cumulative constraint was proposed for modelling cumulative resources in scheduling problems for finite domain (FD) propagation. Since that time a great deal of research has investigated new stronger and faster filtering techniques for cumulative, but still most of these techniques only pay off in limited cases or are not scalable. Recen...

This paper presents the G12 large scale optimisation software platform, and discusses aspects of its architecture.

Symmetries in constraint problems present an opportunity for reducing search. This paper presents Lightweight Dynamic Symmetry Breaking, an automatic symmetry breaking method that is efficient enough to be used as a default, since it never yields a major slowdown while often giving major performance improvements. This is achieved by automatically e...

We describe a small, non-intrusive extension to the declarative modelling language Zinc that allows users to define model-specific search. This is achieved by providing a number of generic search patterns that take Zinc user-defined functions as parameters. We show the generality of the approach by using it to implement three very different kinds o...

Viral marketing is a form of peer-to-peer communication in which individuals are encouraged to pass on promotional messages within their social networks. Conventional wisdom holds that the viral marketing process is both random and unmanageable. In this paper, we deconstruct the process and investigate the formation of the activated digital network...

Zinc is a new modelling language developed as part of the G12 project. It has four important characteristics. First, Zinc allows specication of models using a natural mathematical- like notation. To do so it supports overloaded functions and predicates and automatic coercion and provides arithmetic, nite domain and set constraints. Second, while Zi...

In the service industry, only one thing is certain - next year will be different from this year. Every service operation must therefore continually reallocate resources, reconfigure and reoptimise. Strategy is about where to invest - balancing capital investment against future operating costs. With the resources more or less fixed, the tactical que...

The G12 project is developing a software environment for stating and solving combinatorial problems by mapping a high-level model of the problem to an efficient combination of solving methods. Model annotations are used to control this process. In this paper we explain the mapping to branch-and-price solving. G12 supports the selection of specialis...

While several powerful methods exist for automatically detecting symmetries in instances of constraint satisfaction problems (CSPs), current methods for detecting symmetries in CSP models are limited to the kind of symmetries that can be inferred from the global constraints present in the model. Herein, a new approach for detecting symmetries in CS...

We describe a preliminary implementation of the high-level modelling language Zinc. This language supports a modelling methodology in which the same Zinc model can be automatically mapped into different design models, thus allowing modellers to easily “plug and play” with different solving techniques and so choose the most appropriate for that prob...

Constraint logic programming lies at the intersection of logic programming, optimisation and artificial intelligence. It has proved a successful tool in many areas including production planning, transportation scheduling, numerical analysis and bioinformatics. Eclipse is one of the leading software systems that realise its underlying methodology. E...

We describe the Zinc modelling language. Zinc provides set constraints, user defined types, constrained types, and polymorphic predicates and functions. The last allows Zinc to be readily extended to different application domains by user-defined libraries. Zinc is designed to support a modelling methodology in which the same conceptual model can be...

This paper presents constraint programming (CP) as a natural formalism for modelling problems, and as a flexible platform for solving them. CP has a range of techniques for handling constraints including several forms of propagation and tailored algorithms for global constraints. It also allows linear programming to be combined with propagation and...

This paper surveys hybrid algorithms from a constraint programming perspective. It introduces techniques used within a constructive search framework, such as propagation and linear relaxation, as well as techniques used in combination with search by repair.

Many problems can be formulated in terms of satisfying a set of constraints. This chapter focuses on methods for modeling and solving such problems used in artificial intelligence and implemented in constraint programming languages.

Constraint satisfaction problems are ubiquitous. A simple example that we will use throughout the first half of this chapter is the following scheduling problem: Choose employees A or B for each of three tasks, X, Y, Z, subject to the work rules that the same employee cannot carry out both tasks X and Y, the same employee cannot carry out both task...

The logic programming language Mercury is designed to sup- port programming in the large. Programmer declarations in conjunction with powerful compile-time analysis and optimization allow Mercury pro- grams to be very efficient. The original design of Mercury did not support constraint logic programming (CLP). This paper describes the extensions we...

Mark Wallace is the author, most recently, of a novel, Dead Carnival (Avec), a multi-genre collection, Haze (Edge), and a book of poems, Temporary Worker Rides A Subway (Green Integer).

The G12 project recently started by National ICT Australia (NICTA) is an ambitious project to develop a software platform for solving large scale industrial combinatorial optimisation problems. The core design involves three languages: Zinc, Cadmium and Mercury (Group 12 of the periodic table). Zinc is a declarative modelling language for expressi...

When a major road traffic intersection is blocked, vehicles should be diverted from the incoming roads in such a way as to avoid the roads on the diversions from also becoming over-congested. Assuming different diversions may use partly the same roads, the challenge is to satisfy the following traffic flow constraint: ensure that even in the worst...

The comparative study published in this journal by Fernandez and Hill benchmarked some constraint programming systems on a set of well-known puzzles. The current article examines the positive and negative aspects of this kind of benchmarking. The article analyses some pitfalls in benchmarking, recalling previous published results from benchmarking...

This chapter discusses current and future research directions for the integration of AI and OR techniques in Constraint Programming. We describe the challenges driving this research area, outlining some of the areas where much remains to be done to meet real-world needs. We then investigate the task of mapping problems to solutions, listing the ste...

Recent advances in merging Operations Research (OR) models and methods in Constraint Programming (CP) have stressed the need for programming language implementations which support and facilitate the development of hybrid solvers for combinatorial optimization problems. An important requirement on these implementations is that they distinguish the s...

One strand of CP research seeks to design a small set of primitives and operators that can be used to build an appropriate algorithm for solving any given combinatorial problem. The aim is to “package” CP, simplifying its use, in contrast to current systems which offer application developers a full constraint programming language. In this talk we e...

Constraint Logic Programming (CLP) extends logic programming in two ways. Firstly it admits special predicates called constraints, which are not defined by clauses, but which are handled instead by specific constraint solvers built into the CLP system. This extension has been formalised as the CLP Scheme. Secondly CLP admits other forms of processi...

references to major research papers and projects. Some might find his survey too shallow and broad in certain respects, but I personally found his treatment fair and complete. In subsequent chapters, Wallace introduces a formal query language, called D&Qs, based on referring phrases (Descriptions) and qualifying phrases (Qualifters). He then uses t...

Benders Decomposition is a form of hybridisation that allows linear programming to be combined with other kinds of algorithms. It extracts new constraints for one subproblem from the dual values of the other subproblem. This paper describes an implementation of Benders Decomposition, in the ECLiPSe language, that enables it to be used within a cons...

Constraint Logic Programming (CLP) extends logic programming in two ways. Firstly it admits special predicates called constraints, which are not defined by clauses, but which are handled instead by specific constraint solvers built into the CLP system. This extension has been formalised as the CLP Scheme. Secondly CLP admits other forms of processi...

Benders Decomposition is a form of hybridisation that allows linear programming to be combined with other kinds of algorithms. It extracts new constraints for one subproblem from the dual values of the other subproblem. This paper describes an implementation of Benders Decomposition, in the ECLiPSe language, that enables it to be used within a cons...

This paper describes an algorithm designed to minimally reconfigure schedules in response to a changing environment. External factors have caused an existing schedule to become invalid, perhaps due to the withdrawal of resources, or because of changes to the set of scheduled activities. The total shift in the start and end times of already schedule...

Costly general decision procedures can be sped up by incorporating efficient decision procedures for restricted classes of constraints. We show how to make use of these specialized decision procedures by constructing a network of cooperating decision procedures. Of course, in order to gain efficiency the expensive general decision procedures should...

Constraint logic programming is often described as logic programming with unification replaced by constraint solving over a computation domain. There is another, very different, CLP paradigm based on constraint satisfaction, where program-defined goals can be treated as constraints and handled using propagation. This paper proposes a generalisation...

Constraint logic programming is often described as logic programming with unification replaced by constraint solving over a computation domain. There is another, very different, CLP paradigm based on constraint satisfaction, where program-defined goals can be treated as constraints and handled using propagation. This paper proposes a generalisation...

. This paper describes an algorithm designed to minimally recongure schedules in response to a changing environment. External factors have caused an existing schedule to become invalid, perhaps due to the withdrawal of resources, or because of changes to the set of scheduled activities. The total shift in the start and end times of already schedule...

This issue of IEEE Intelligent Systems includes an interview with Pierre Haren and Mehmet Dincbas, the heads of ILOG and Cosytec, two major commercial vendors of constraint technology. Constraint technology has made a significant industrial impact. Many industrial scheduling problems use constraints, especially problems that require fine-grained sc...

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Benchmark comparisons tend to overlook the most important challenge in solving combinatorial problems: how to design an appropriate algorithm. For example an early version of Localizer incurred a factor 3 performance penalty when bench-marked against a 'C implementation of GSAT, but I would recommend implementing a new local search algorithm in Loc...

We investigate some useful strategies for solving a vari- ety of hard search problems. In the process we identify weaknesses in the standard CSP formalisation of such problems.

this document is the metaterm.

The workshop will be held in conjunction with the www.di.unipi.it/cp98/, Fourth International Conference on Principles and Practice of Constraint Programming (CP98), October 26 - 30, 1998. Program: This workshop will explore hybrid algorithms for complex optimisation problems. These will be based on the integration of different approaches, viz. con...

Despite a lot of recent interest in purely functional data structures, for example [Ada93, Oka95, BO96, Oka96, OB97, Erw97], few have been benchmarked. Of these, even fewer have their performance qualified by how they are used. But how a data structure ...

This paper represents an integration of Mixed Integer Programming (MIP) and ConstraintLogic Programming (CLP) which, like MIP, tightens bounds rather than adding constraintsduring search. The integrated system combines components of the CLP system ECLiPSe[7] and the MIP system CPLEX [5], in which constraints can be handled by either one orboth comp...

This paper presents a robust approach to solve Hoist Scheduling Problems (HSPs) based on an integration of Constraint Logic Programming (CLP) and Mixed Integer Programming (MIP). By contrast with previous dedicated models and algorithms for solving classes of HSPs, we define only one model and run different solvers The robust approach is achieved b...

. Constraint propagation algorithms vary in the strength of propagation they apply. This paper investigates a simple configuration for adaptive propagation -- the process of varying the strength of propagation to reflect the dynamics of search. We focus on two propagation methods, Arc Consistency (AC) and Forward Checking (FC). AC-based algorithms...

. This paper describes an algorithm, unimodular probing, conceived to optimally reconfigure schedules in response to a changing environment. In the problems studied, resources may become unavailable, and scheduled activities may change. The total shift in the start and end times of activities should be kept to a minimum. This requirement is capture...

This paper describes our experience in implementing an industrial application using thefinite domain solver of the ECLi PSe constraint logic programming (CLP) system, inconjunction with the mathematical programming (MP) system, FortMP. In this technique,the ECLi PSe system generates a feasible solution that is adapted to construct a starting point(...

Introduction Constraint programming is a paradigm that is tailored to hard search problems. To date the main application areas are those of planning, scheduling, timetabling, routing, placement, investment, configuration, design and insurance. Constraint programming incorporates techniques from mathematics, artificial intelligence and operations re...

This paper describes an algorithm, unimodular probing, conceived to optimally reconfigure schedules in response to a changing environ- ment. In the problems studied, resources may become unavailable, and scheduled activities may change. The total shift in the start and end times of activities should be kept to a minimum. This require- ment is captu...

Constraints programming is well-placed to take a key role in the development of distributed scheduling systems. Problem constraints can be directly encoded as program constraints. Specialised algorithms can be naturally embedded and - more importantly - they can be concurrently executed as active constraints. Finally constraint-based computation pr...