In this paper we discuss the integration of logic, modeling, and programming in order to solve problems in operations research, artificial intelligence, and decision support programming in general. Our goals are to in...
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In this paper we discuss the integration of logic, modeling, and programming in order to solve problems in operations research, artificial intelligence, and decision support programming in general. Our goals are to integrate modeling into the larger programming scheme of things and, conversely, to inject programming into modeling. To accomplish these ends, we use the language 2LP, which is based on ideas from constraint logic programming. This leads to a technologically open way to handle problems, one which supports flexible treatment of goal programming, hybrid MIP/local search algorithms, libraries for distributed processing, disjunctive programming, etc. An additional advantage of the programming language approach is that problem solving and model management can be abetted by software engineering techniques. In this paper, by means of variations on a single example, we will illustrate how the logical connectives and linear constraints interact in the solution of a linear program, a goal program, a disjunctive program, a branch and bound search, a randomized shuffle algorithm, and a parallel solution to a model with stochastic data.
It appears that classical logic is not suitable for the representation and reasoning about knowledge of disposable resources. The major difference between reasoning about disposable resources and classical logic is th...
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It appears that classical logic is not suitable for the representation and reasoning about knowledge of disposable resources. The major difference between reasoning about disposable resources and classical logic is that once a disposable resource is used to produce something, it is not available any more;but a formula of classical logic can be repeatedly used in deduction. Inspired by linear logic, or logic of resources, we propose a language for knowledge-based systems of resources, which can process state space models of systems represented by Petri nets or their subclasses such as marked graphs and state machines. It can serve as a modeling tool for various engineering and social science problems of resource allocations.
This paper presents a hybrid approach for sealed bid auction that integrates linear programming and logic modeling techniques. A linear programming model for the sealed bid auction considers only prices for transactio...
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This paper presents a hybrid approach for sealed bid auction that integrates linear programming and logic modeling techniques. A linear programming model for the sealed bid auction considers only prices for transaction arrangements and yields multiple market cores when goods from sellers are equally attractive to many buyers. The hybrid approach takes into account ordinal preferences of traders as well to find the best market core. On the one hand, the hybrid approach uses a linear programming model to maximize total surplus of market participants based on the bid and ask prices. On the other hand, it employs a logical inferencing approach to satisfy traders' ordinal preferences that are not included in a single combination of bid and ask prices. A constraint logic programming scheme, which combines a mathematical program with a logical inferencing technique in an integrated formalism, is introduced to implement the hybrid approach. The hybrid approach is validated through market simulations, where a set of computer-generated trading data is applied to both the hybrid approach and the linear programming model for their market performance comparison.
This paper deals with scheduling problem in electroplating facilities. To maximise the productivity of electroplating lines, a predictive approach can be used to find a sequence of hoist movements that can be cyclical...
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This paper deals with scheduling problem in electroplating facilities. To maximise the productivity of electroplating lines, a predictive approach can be used to find a sequence of hoist movements that can be cyclically repeated. This NP-hard problem is known as the Cyclic Hoist Scheduling Problem. An approach for the multi-hoists problem is suggested. The presented model uses constraint logic programming for finding the optimal cyclic schedule for a given hoist assignment.
We define value constraints, a method for incorporating constraint propagation into logicprogramming. It is a subscheme of the CLP scheme and is applicable wherever one has an efficient method for representing sets o...
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We define value constraints, a method for incorporating constraint propagation into logicprogramming. It is a subscheme of the CLP scheme and is applicable wherever one has an efficient method for representing sets of possible values. As examples we present: small finite sets, sets of ground instances of a term, and intervals of reals with floating-point numbers as bounds. Value constraints are defined by distinguishing two storage management strategies in the CLP scheme. In value constraints the infer step of the CLP scheme is implemented by Waltz filtering. We give a semantics for value constraints in terms of set algebra that gives algebraic characterizations of local and global consistency. The existing extremal fixpoint characterization of chaotic iteration is shown to be applicable to prove convergence of Waltz filtering.
A system which extracts a dataflow graph from sets of arithmetic constraints is described. This information is used to simplify constraints and to extract positive information from negations of constraints. The contex...
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A system which extracts a dataflow graph from sets of arithmetic constraints is described. This information is used to simplify constraints and to extract positive information from negations of constraints. The context for this work is a Prolog implementation where intervals are used to represent the underlying arithmetic variables. The system uses simple information about the existence of solutions of primitive constraints to derive the dataflow graph. This makes the system easily extensible to new primitives and domains. A practical implementation over both real and integer arithmetic is described and an extended example of its application given.
This paper presents a technique to map automatically a complete digital signal processing (DSP) application onto a parallel machine with distributed memory. Unlike other applications where coarse or medium grain sched...
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ISBN:
(纸本)0818679581
This paper presents a technique to map automatically a complete digital signal processing (DSP) application onto a parallel machine with distributed memory. Unlike other applications where coarse or medium grain scheduling techniques can be used DSP applications integrate several thousand of tasks and hence necessitate fine grain considerations. Moreover finding an effective mapping imperatively require to take into account both architectural resources constraints and real time constraints. The main contribution of this paper is to show how it as possible to handle and to solve data partitioning, and fine-grain scheduling under the above operational constraints using Concurrent constraints logicprogramming languages (CCLP). Our concurrent resolution technique undertaking linear and non linear constraints takes advantage of the special features of signal processing applications and provides a solution equivalent to a manual solution for the representative Panoramic Analysis (PA) application.
Much recent work has focused on the bottom-up evaluation of Datalog programs [Bancilhon and Ramakrishnan 1988]. One approach, called magic-sets, is based on rewriting a logic program so that bottom-up fixpoint evaluat...
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Much recent work has focused on the bottom-up evaluation of Datalog programs [Bancilhon and Ramakrishnan 1988]. One approach, called magic-sets, is based on rewriting a logic program so that bottom-up fixpoint evaluation of the program avoids generation of irrelevant facts [Bancilhon et al. 1986;Beeri and Ramakrishnan 1987;Ramakrishnan 1991]. It was widely believed for some time that the principal application of the magic-sets technique is to restrict computation in recursive queries using equijoin predicates. We extend the magic-sets transformation to use predicates other than equality (X > 10, for example) in restricting computation. The resulting ground magic-sets transformation is an important step in developing an extended magic-sets transformation that has practical utility in ''real'' relational databases, not only for recursive queries, but for nonrecursive queries as well [Mumick et al. 1990b;Mumick 1991].
In this paper, the notion of the Anticipatory Pruning Network (APN) is introduced and developed for the propositional part of the 2LP system;2LP (Linear programming and logicprogramming) is a constraintlogic program...
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In this paper, the notion of the Anticipatory Pruning Network (APN) is introduced and developed for the propositional part of the 2LP system;2LP (Linear programming and logicprogramming) is a constraint logic programming system which has been developed and implemented at the logic Based System Lab at Brooklyn College/CUNY. Using the compilation of rules in the style of the Rete algorithm, the APN maps program clauses into a network, The APN prunes a search space by consistency checking and inconsistency propagation through the network and resets itself upon backtracking. The APN extends forward checking to continuous constraint domains, Overall, the benchmarks show the APN to be an effective forward checking mechanism for both discrete and continuous problem domains for Simplex based constraint solvers. In particular, the APN is an effective pruning method for constrained mixed integer, linear optimization problems.
In this paper, we describe Nicolog, a language with capabilities similar to recently developed constraint logic programming (CLP) languages such as CLP(BNR), clp(FD), and cc(FD). Central to Nicolog are projection cons...
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In this paper, we describe Nicolog, a language with capabilities similar to recently developed constraint logic programming (CLP) languages such as CLP(BNR), clp(FD), and cc(FD). Central to Nicolog are projection constraints (PCs), a sublanguage for compiling and optimizing constraint propagation in numeric and Boolean domains. PCs are an interesting generalization of the indexical constraints introduced in cc(FD) and also found in clp(FD). Nicolog compiles a very general class of built-in constraints into equivalent sets of PCs, allowing an arbitrary mixture of integer (easily extensible to real) and Boolean operations. Nicolog also lets the user program PCs directly, making it possible to implement new sophisticated propagation procedures. We show that PCs are a simple, efficient, and flexible way to implement most of the propagation procedures possible in other FD CLP systems. These include procedures for cardinality, constructive disjunction, implication, and mixed Boolean/numeric constraints. Empirical results with a simple prototype Nicolog implementation based on the WAM architecture show it can solve hard problems with speed comparable to the fastest existing CLP systems.
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