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PathBased Scheduling for Synthesis
 IEEE TRANSACTIONS ON COMPUTERAIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
, 1991
"... In the context of synthesis, scheduling assigns operations to control steps. Operations are the atomic components used for describing behavior, for example, arithmetic and Boolean operations. They are ordered partially by data dependencies (dataflow graph) and by control constructs such as condit ..."
Abstract

Cited by 87 (0 self)
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In the context of synthesis, scheduling assigns operations to control steps. Operations are the atomic components used for describing behavior, for example, arithmetic and Boolean operations. They are ordered partially by data dependencies (dataflow graph) and by control constructs such as conditional branches and loops (controlflow graph). A control step usually corresponds to one state, one clock cycle, or one microprogram step. This paper presents a new, pathbased scheduling algorithm. It yields solutions with the minimum number of control steps, taking into account arbitrary constraints that limit the amount of operations in each control step. The result is a finite state machine that implements the control. Although the complexity of the algorithm is proportional to the number of paths in the controlflow graph, it is shown to be practical for large examples with thousands of nodes.
The ant colony optimization metaheuristic: Algorithms, applications, and advances
 Handbook of Metaheuristics
, 2002
"... ..."
Fuzzy Constraints in JobShop Scheduling
 Journal of Intelligent Manufacturing
, 1995
"... : This paper proposes an extension of the constraintbased approach to jobshop scheduling, that accounts for the flexibility of temporal constraints and the uncertainty of operation durations. The set of solutions to a problem is viewed as a fuzzy set whose membership function reflects preference. ..."
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Cited by 53 (9 self)
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: This paper proposes an extension of the constraintbased approach to jobshop scheduling, that accounts for the flexibility of temporal constraints and the uncertainty of operation durations. The set of solutions to a problem is viewed as a fuzzy set whose membership function reflects preference. This membership function is obtained by an egalitarist aggregation of local constraintsatisfaction levels. Uncertainty is qualitatively described is terms of possibility distributions. The paper formulates a simple mathematical model of jobshop scheduling under preference and uncertainty, relating it to the formal framework of constraintsatisfaction problems in Artificial Intelligence. A combinatorial search method that solves the problem is outlined, including fuzzy extensions of wellknown lookahead schemes. 1. Introduction There are traditionally three kinds of approaches to jobshop scheduling problems: priority rules, combinatorial optimization and constraint analysis. The first kind ...
Adaptive Critic Design of Control Policies for a MultiEchelon Inventory
, 2000
"... A common problem in business is the determination of inventory and transpotation policies for a physical distribution system within a changing business environment. This dissertation addresses the process of selecting an optimal set of policies for a multiproduct, multiechelon, multimodal physi ..."
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Cited by 2 (1 self)
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A common problem in business is the determination of inventory and transpotation policies for a physical distribution system within a changing business environment. This dissertation addresses the process of selecting an optimal set of policies for a multiproduct, multiechelon, multimodal physical distribution system in a nonstationary environment. The problem is highly multidimensional, even with a small system, and the fitness surface is quite often discontinuous, with low penalty and high penalty regions separated by no more than a single transport unit. A controller design process is presented that reliably improves on the performance of the typical fixedpolicy controllers. The design process has two basic stages. First, a Genetic Algorithm (GA) is used to perform a global search (in a static environment) to find a good initial policy to be used as a starting point by the next stage. Second, an approximate dynamic programming method, implemented by an adaptive critic method known as Dual Heuristic Programming (DHP), is used to perform local optimization and fitnessterrain
An improved constraint satisfaction adaptive neural network for jobshop scheduling
, 2010
"... This paper presents an improved constraint satisfaction adaptive neural network for jobshop scheduling problems. The neural network is constructed based on the constraint conditions of a jobshop scheduling problem. Its structure and neuron connections can change adaptively according to the realt ..."
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This paper presents an improved constraint satisfaction adaptive neural network for jobshop scheduling problems. The neural network is constructed based on the constraint conditions of a jobshop scheduling problem. Its structure and neuron connections can change adaptively according to the realtime constraint satisfaction situations that arise during the solving process. Several heuristics are also integrated within the neural network to enhance its convergence, accelerate its convergence, and improve the quality of the solutions produced. An experimental study based on a set of benchmark jobshop scheduling problems shows that the improved constraint satisfaction adaptive neural network outperforms the original constraint satisfaction adaptive neural network in terms of computational time and the quality of schedules it produces. The neural network approach is also experimentally validated to outperform three classical heuristic algorithms that are widely used as the ba
for jobshop scheduling
, 2007
"... An improved constraint satisfaction adaptive neural network ..."
1 Gradual Numbers and their Application to Fuzzy Interval Analysis
"... Abstract — We introduce a new way of looking at fuzzy intervals. Instead of considering them as fuzzy sets, we see them as crisp sets of entities we call gradual (real) numbers. They are a gradual extension of real numbers, not of intervals. Such a concept is apparently missing in fuzzy set theory. ..."
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Abstract — We introduce a new way of looking at fuzzy intervals. Instead of considering them as fuzzy sets, we see them as crisp sets of entities we call gradual (real) numbers. They are a gradual extension of real numbers, not of intervals. Such a concept is apparently missing in fuzzy set theory. Gradual numbers basically have the same algebraic properties as real numbers, but they are functions. A fuzzy interval is then viewed as a pair of fuzzy thresholds, which are monotonic gradual real numbers. This view enable interval analysis to be directly extended to fuzzy intervals, without resorting tocuts, in agreement with Zadeh’s extension principle. Several results show that interval analysis methods can be directly adapted to fuzzy interval computation where end points of intervals are changed into left and right fuzzy bounds. Our approach is illustrated on two known problems: computing fuzzy weighted averages, and determining fuzzy floats and latest starting times in activity network scheduling. I.