Multi-stage decision problems under uncertainty are abundant in process industries. Markov decision process (MDP) is a general mathematical formulation of such problems. Whereas stochastic programming and dynamic prog...
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Multi-stage decision problems under uncertainty are abundant in process industries. Markov decision process (MDP) is a general mathematical formulation of such problems. Whereas stochastic programming and dynamic programming are the standard methods to solve MDPs, their unwieldy computational requirements limit their usefulness in real applications. Approximate dynamic programming (ADP) combines simulation and function approximation to alleviate the 'curse-of-dimensionality' associated withthe traditional dynamic programming approach. In this paper, we present the ADP as a viable way to solve MDPs for process control and scheduling problems. We bring forth some key issues for its successful application in these types of problems, including the choice of function approximator and the use of a penalty function to guard against over-extending the value function approximation in the value iteration. Application studies involving a number of well-known control and scheduling problems, including dual control, multiple controller scheduling, and resource constrained project scheduling problems, point to the promising potentials of ADP. (c) 2006 Elsevier Ltd. All rights reserved.
this paper presents a fuzzy programming approach for solving bi-level multi-objective linear programming problems with a single decision maker at the upper level and multiple decision makers at the lower *** membershi...
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A combination approach of a modified PIPE algorithm to find the best architecture of hierarchical TS fuzzy model for a given problem and a simple evolutionary programming algorithm to optimize the parameters embedded ...
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ISBN:
(纸本)7121002159
A combination approach of a modified PIPE algorithm to find the best architecture of hierarchical TS fuzzy model for a given problem and a simple evolutionary programming algorithm to optimize the parameters embedded in die hierarchical TS fuzzy model is proposed. Simulation result for the chaotic time-series prediction problem show the feasibility and effectiveness of the proposed method.
It is known that traditional education is teacher-centered, which is associated chiefly withthe transmission of knowledge. It is very hard to raise students' interests and inspire their motives to learn. Conseque...
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the proceedings contain 34 papers. the special focus in this conference is on functionalprogramming and Narrowing. the topics include: A generic program for sequential decision processes;parsing visual languages with...
ISBN:
(纸本)354060359X
the proceedings contain 34 papers. the special focus in this conference is on functionalprogramming and Narrowing. the topics include: A generic program for sequential decision processes;parsing visual languages with constraint multiset grammars;programming with constructor classes;towards a taxonomy of functional language implementations;a verified implementation of narrowing;a new calculus for semantic matching;a complete narrowing calculus for higher-order functional logic programming;exploiting parallelism in tabled evaluations;design and implementation of jump tables for fast indexing of logic programs;an abstract machine for Oz;uniform PERs and comportment analysis;uniqueness type inference;mode analysis of arrays and array comprehensions;better consumers for deforestation;efficient compile-time garbage collection for arbitrary data structures;efficient multi-level generating extensions;mechanically verifying the correctness of an offline partial evaluator;a semantic model of binding times for safe partial evaluation;lazy functional components for graphical user interfaces;lightweight GUIs for functionalprogramming;lazy functional components for graphical user interfaces;lightweight GUIs for functionalprogramming;a functional framework for deterministically interleaved interactive programs;a debugging model for lazy narrowing;evaluation of expressions in a multiparadigm framework;an expression-or-parallel implementation for a functional logic language;attributed models of executable specifications;approximating constraint logic programs using polymorphic types and regular descriptions;performance of a data-parallel concurrent constraint programming system and a portable implementation of memoing evaluation.
this paper introduces a type-preserving XML Schema-Haskell data binding (or, translation) UUXML, and shows how to customize it by exploiting the theory of canonical isomorphisms to automatically infer coercions betwee...
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this paper introduces a type-preserving XML Schema-Haskell data binding (or, translation) UUXML, and shows how to customize it by exploiting the theory of canonical isomorphisms to automatically infer coercions between the machine-generated types and an equivalent, more natural, user-defined set of types. We show how to implement the inference mechanism in Generic Haskell. (c) 2006 Elsevier B.V. All rights reserved.
In this paper, we propose a hierarchical timing-driven Steiner tree algorithm for global routing which considers the minimization of timing, delay during the tree construction as the goal. the algorithm uses heuristic...
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ISBN:
(纸本)0769514413
In this paper, we propose a hierarchical timing-driven Steiner tree algorithm for global routing which considers the minimization of timing, delay during the tree construction as the goal. the algorithm uses heuristic approach to decompose the problem of minimum delay Steiner free into hierarchy and to construct the sub-trees respectively based on dynamic programming technique. Taking the net topology into consideration, we build the final routing tree by reconnecting, the sub-trees at each level recursively and then improve the connection withthe objective of minimizing the delay from source to sink pins on the critical path. Meanwhile, some efficient strategies have been proposed to speed up the solving process. Experimental results are given to demonstrate the efficiency of the algorithm.
the rising operating cost of power systems and over-utilization of fossil fuel deposits have led to continuous energy scarcity and a wide gap between energy demand and supply. these pose critical challenges across the...
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ISBN:
(纸本)9781538654316
the rising operating cost of power systems and over-utilization of fossil fuel deposits have led to continuous energy scarcity and a wide gap between energy demand and supply. these pose critical challenges across the world. the renewable energy sources (RESs) provide a viable and sustainable energy alternative which is capable of meeting the exponential energy growth, reducing over-dependency on fossil fuels as well as minimizing global warming. this paper presents an optimal control and management of an autonomous hybrid energy system (AHES) that reliably supplies energy demand at a minimum daily operating cost. the non-linear cost function is formulated as a mixed integer nonlinear programming (MINLP) problem to optimize the use of renewable resources and minimize the utilization of diesel generator (DG). the unpredictability inherent in RESs is addressed through the optimal design and management of multiple energy generation sources, and battery storage system (BSS). the MINLP optimization technique employed is validated with a dynamic commercial daily load profiles. the simulation results show that the proposed hybrid system significantly minimizes daily operating cost and improves supply reliability when compared to DG-single system.
In the realm of ride-hailing platforms, the ability to anticipate passenger demand in various regions and suggest routes withthe highest demand to drivers plays a pivotal role. While this mechanism optimizes system e...
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ISBN:
(纸本)9798400716348
In the realm of ride-hailing platforms, the ability to anticipate passenger demand in various regions and suggest routes withthe highest demand to drivers plays a pivotal role. While this mechanism optimizes system efficiency, it causes income disparity among the drivers leading to varying earnings even when their working hours align. Recent research that has focused on addressing fairness issues in ridesharing platforms has primarily concentrated on developing matching algorithms to pair rider requests with available drivers. However, there has been no work on the development of fair route recommendation systems for ridesharing platforms. In response to this gap, we introduce a novel approach that incorporates fairness into the design of route recommendation systems. Our proposed model utilizes dynamic programming-based relocation approach and a priority framework for providing fair routes to drivers.
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