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Planning Under Time Constraints in Stochastic Domains
 ARTIFICIAL INTELLIGENCE
, 1993
"... We provide a method, based on the theory of Markov decision processes, for efficient planning in stochastic domains. Goals are encoded as reward functions, expressing the desirability of each world state; the planner must find a policy (mapping from states to actions) that maximizes future reward ..."
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Cited by 163 (19 self)
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We provide a method, based on the theory of Markov decision processes, for efficient planning in stochastic domains. Goals are encoded as reward functions, expressing the desirability of each world state; the planner must find a policy (mapping from states to actions) that maximizes future rewards. Standard goals of achievement, as well as goals of maintenance and prioritized combinations of goals, can be specified in this way. An optimal policy can be found using existing methods, but these methods require time at best polynomial in the number of states in the domain, where the number of states is exponential in the number of propositions (or state variables). By using information about the starting state, the reward function, and the transition probabilities of the domain, we restrict the planner's attention to a set of world states that are likely to be encountered in satisfying the goal. Using this restricted set of states, the planner can generate more or less complete ...
Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems
, 1998
"... We use a local search method we term Large Neighbourhood Search (LNS) for solving vehicle routing problems. LNS meshes well with constraint programming technology and is analogous to the shuffling technique of jobshop scheduling. The technique explores a large neighbourhood of the current solution ..."
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Cited by 139 (2 self)
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We use a local search method we term Large Neighbourhood Search (LNS) for solving vehicle routing problems. LNS meshes well with constraint programming technology and is analogous to the shuffling technique of jobshop scheduling. The technique explores a large neighbourhood of the current solution by selecting a number of customer visits to remove from the routing plan, and reinserting these visits using a constraintbased tree search. We analyse the performance of LNS on a number of vehicle routing benchmark problems. Unlike related methods, we use Limited Discrepancy Search during the tree search to reinsert visits. We also maintain diversity during search by dynamically altering the number of visits to be removed, and by using a randomised choice method for selecting visits to remove. We analyse the performance of our method for various parameter settings controlling the discrepancy limit, the dynamicity of the size of the removal set, and the randomness of the choice. We demonst...
Dynamic instabilities and stabilization methods in distributed realtime scheduling of manufacturing systems
 IEEE Transactions on Automatic Control
, 1990
"... z Abstract We consider manufacturing systems consisting of many machines and producing many types of parts. Each parttype requires processing for a specified length of time at each machine in a prescribed sequence of machines. Machines may require a setup time when changing between parttypes, and ..."
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Cited by 100 (18 self)
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z Abstract We consider manufacturing systems consisting of many machines and producing many types of parts. Each parttype requires processing for a specified length of time at each machine in a prescribed sequence of machines. Machines may require a setup time when changing between parttypes, and parts may incur a variable transportation delay when moving between machines. The goal is to dynamically schedule all the machines so that all the parttypes are produced at the desired rates while maintaining bounded buffer sizes at all machines. In this paper we study the interaction of two types of feedbacks, one caused by "cycles " of material flow in nonacyclic manufacturing systems, and the other introduced by the employment of closedloop scheduling algorithms. We examine the consequences of this interaction for the stability properties of the manufacturing system in terms of maintaining bounded buffer levels. First, we resolve a previously open problem by exhibiting the instability of all "clearing policies " for some nonacyclic manufacturing
Improved CLP Scheduling with Task Intervals
, 1994
"... In this paper we present a new technique that can be used to improve performance of job scheduling with a constraint programming language. We show how, by focusing on some special sets of tasks, one can bring CLP in the same range of efficiency as traditional OR algorithms on a classical benchmark ( ..."
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Cited by 95 (6 self)
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In this paper we present a new technique that can be used to improve performance of job scheduling with a constraint programming language. We show how, by focusing on some special sets of tasks, one can bring CLP in the same range of efficiency as traditional OR algorithms on a classical benchmark (MT10 [MT63]), thus making CLP both a flexible and an efficient technique for such combinatorial problems. We then present our programming methodology which we have successfully used on many problems, and draw conclusions on what features constraint programming languages should offer to allow its use. 1. Introduction Reallife scheduling problems are often the composition of various wellidentified hard problems. In the previous years, we have worked on applications such as tasktechnician assignments [CK92] or staff timetable scheduling [CGL93] and developed a methodology for solving such problems with an extensible constraint logic programming language. In both cases we have applied the s...
A New Approach to Computing Optimal Schedules for the JobShop Scheduling Problem
 In Proc. of the 5th International IPCO Conference
, 1996
"... . From a computational point of view, the jobshop scheduling problem is one of the most notoriously intractable NPhard optimization problems. In spite of a great deal of substantive research, there are instances of even quite modest size for which it is beyond our current understanding to solv ..."
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Cited by 78 (0 self)
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. From a computational point of view, the jobshop scheduling problem is one of the most notoriously intractable NPhard optimization problems. In spite of a great deal of substantive research, there are instances of even quite modest size for which it is beyond our current understanding to solve to optimality. We propose several new lower bounding procedures for this problem, and show how to incorporate them into a branchandbound procedure. Unlike almost all of the work done on this problem in the past thirty years, our enumerative procedure is not based on the disjunctive graph formulation, but is rather a timeoriented branching scheme. We show that our approach can solve most of the standard benchmark instances, and obtains the best known lower bounds on each. 1 Introduction In the jobshop scheduling problem we are given a set of n jobs, J , a set of m machines, M, and a set of operations, O. Each job consists of a chain of operations, let O j be the chain of operati...
Deterministic JobShop Scheduling: Past, Present and Future
 European Journal of Operational Research
, 1998
"... : Due to the stubborn nature of the deterministic jobshop scheduling problem many solutions proposed are of hybrid construction cutting across the traditional disciplines. The problem has been investigated from a variety of perspectives resulting in several analytical techniques combining generic ..."
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Cited by 68 (2 self)
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: Due to the stubborn nature of the deterministic jobshop scheduling problem many solutions proposed are of hybrid construction cutting across the traditional disciplines. The problem has been investigated from a variety of perspectives resulting in several analytical techniques combining generic as well as problem specific strategies. We seek to assess a subclass of this problem in which the objective is minimising makespan, by providing an overview of the history, the techniques used and the researchers involved. The sense and direction of their work is evaluated by assessing the reported results of their techniques on the available benchmark problems. From these results the current situation and pointers for future work are provided. KEYWORDS: Scheduling Theory; JobShop; Review; Computational Study; 1. INTRODUCTION Current market trends such as consumer demand for variety, shorter product life cycles and competitive pressure to reduce costs have resulted in the need for zero i...
A Theoretical and Experimental Comparison of Constraint Propagation Techniques for Disjunctive Scheduling
, 1995
"... Disjunctive constraints are widely used to ensure that the time intervals over whichtwo activities require the same resource cannot overlap: if a resource is required bytwo activities A and B, the disjunctive constraint states that either A precedes B or B precedes A. The #propagation " of di ..."
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Cited by 59 (8 self)
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Disjunctive constraints are widely used to ensure that the time intervals over whichtwo activities require the same resource cannot overlap: if a resource is required bytwo activities A and B, the disjunctive constraint states that either A precedes B or B precedes A. The #propagation " of disjunctive constraints consists in determining cases where only one of the two orderings is feasible. It results in updating the timebounds of the two activities. The standard algorithm for propagating disjunctive constraints achieves arcBconsistency.Twotypes of methods that provide more precise timebounds are studied and compared. The #rst type of method consists in determining whether an activity A must, can, or cannot be the #rst or the last to execute among a set of activities that require the same resource. The second consists in comparing the amount of #resource energy" required over a time interval #t 1 t 2 #to the amount of energy that is available over the same interval. The main result of the study is an implementation of the #rst method in Ilog Schedule, a generic tool for constraintbased scheduling which exhibits performance in the same range of e#ciency as speci#c operations research algorithms.
Project scheduling under uncertainty: Survey and research potentials
 European Journal of Operational Research
, 2005
"... The vast majority of the research efforts in project scheduling assume complete information about the scheduling problem to be solved and a static deterministic environment within which the precomputed baseline schedule will be executed. However, in the real world, project activities are subject to ..."
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Cited by 58 (3 self)
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The vast majority of the research efforts in project scheduling assume complete information about the scheduling problem to be solved and a static deterministic environment within which the precomputed baseline schedule will be executed. However, in the real world, project activities are subject to considerable uncertainty, which is gradually resolved during project execution. In this survey we review the fundamental approaches for scheduling under uncertainty: reactive scheduling, stochastic project scheduling, fuzzy project scheduling, robust (proactive) scheduling and sensitivity analysis. We discuss the potentials of these approaches for scheduling under uncertainty projects with deterministic network evolution structure. Ó 2004 Elsevier B.V. All rights reserved.
Nonsystematic Backtracking Search
, 1995
"... Many practical problems in Artificial Intelligence have search trees that are too large to search exhaustively in the amount of time allowed. Systematic techniques such as chronological backtracking can be applied to these problems, but the order in which they examine nodes makes them unlikely to fi ..."
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Cited by 54 (1 self)
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Many practical problems in Artificial Intelligence have search trees that are too large to search exhaustively in the amount of time allowed. Systematic techniques such as chronological backtracking can be applied to these problems, but the order in which they examine nodes makes them unlikely to find a solution in the explored fraction of the space. Nonsystematic techniques have been proposed to alleviate the problem by searching nodes in a random order. A technique known as iterative sampling follows random paths from the root of the tree to the fringe, stopping if a path ends at a goal node. Although the nonsystematic techniques do not suffer from the problem of exploring nodes in a bad order, they do reconsider nodes they have already ruled out, a problem that is serious when the density of solutions in the tree is low. Unfortunately, for many practical problems the order of examing nodes matters and the density of solutions is low. Consequently, neither chronological backtracking...
Disjunctive Scheduling with Task Intervals
, 1995
"... .......................................................................................2 Rsum ........................................................................................3 1. Introduction..............................................................................4 2. Disjunctive Sch ..."
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Cited by 50 (1 self)
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.......................................................................................2 Rsum ........................................................................................3 1. Introduction..............................................................................4 2. Disjunctive Scheduling...............................................................4 2.1. Jobshop scheduling.........................................................4 2.2 The branch and bound scheme with time windows..............5 3. Task Intervals and their Application to Scheduling........................6 3.1 Intervals as Sets of Tasks .................................................6 3.2 Reduction with Intervals..................................................8 3.3 Interval Maintenance..................................................... 11 3.4 Comparison with related work ....................................... 13 3.5 Branch & bound ...........................................................