To design supervisors enforcing liveness of automated manufacturing systems (AMS), an efficient deadlock prevention policy based on the exhausted resources is proposed. This policy exploits a special structure of Petr...
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To design supervisors enforcing liveness of automated manufacturing systems (AMS), an efficient deadlock prevention policy based on the exhausted resources is proposed. This policy exploits a special structure of Petri nets in the sense that the liveness of a specific system can be guaranteed if no shared resource can be emptied. In contrast to the typical conventional policies, the explicit enumeration of either the reachable states or the siphons can be avoided. Experimental results verify the efficient implementation of the proposed policy.
This paper proposes an optimization-based method of planning reactive power control for electric transmission systems to endow them with the capability of being reconfigured to a secure configuration under a list of c...
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This paper proposes an optimization-based method of planning reactive power control for electric transmission systems to endow them with the capability of being reconfigured to a secure configuration under a list of contingencies. The overall objective function is to minimize the installation cost of new controls such as mechanically switched capacitors, while satisfying the requirements of voltage stability margin and voltage magnitude under a contingency list. The backward/forward search algorithm with linear complexity is used to select candidate locations for switched capacitors. Optimal locations and amounts of new switch controls are obtained by solving a sequence of mixed integer programming problems. The modified New England 39-bus system and a North American power system with 6358 buses are adopted to illustrate the effectiveness of the proposed method.
Canonical duality theory is a potentially powerful methodology, which can be used to model complex systems with a unified solution to a wide class of discrete and continuous problems in global optimization and nonconv...
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Canonical duality theory is a potentially powerful methodology, which can be used to model complex systems with a unified solution to a wide class of discrete and continuous problems in global optimization and nonconvex analysis. This paper presents a brief review and recent developments of this theory with applications to some well-know problems, including polynomial minimization, mixedinteger and fractional programming, nonconvex minimization with nonconvex quadratic constraints, etc. Results shown that under certain conditions, these difficult problems can be solved by deterministic methods within polynomial times, and NP-hard discrete optimization problems can be transformed to certain minimal stationary problems in continuous space Concluding remarks and open problems are presented in the end. (C) 2009 Elsevier Ltd. All rights reserved.
In recent times, there has been a consistent need for companies to produce 'green' products and offer 'green' services in order to contribute to environmental protection. The utilisation of used device...
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In recent times, there has been a consistent need for companies to produce 'green' products and offer 'green' services in order to contribute to environmental protection. The utilisation of used devices (extending their useful life cycle) is an excellent, indirect way for companies to conform to this requirement and, at the same time, increase their profit. Cell phones constitute one of the most interesting cases of products, which can be returned, remanufactured and reused: their replacement rate is large, the available quantity for reuse is huge and, consequently, the profit potential is significant. Motivated by the real case of a company involved in the acquisition and remanufacturing of used cell phones, a simple mathematical programming model is proposed in this work that can help remanufacturing companies to make optimal decisions concerning the quantities to be purchased and remanufactured. Its use, namely the simulation of the model stochastic parameters and the optimisation of the model, reveals not only that the exploitation of used products can be profitable, but also that as the 'product acquisition system' improves, the economic benefits for any remanufacturing company can be even greater.
Given a product design and a repair network, a level of repair analysis (LORA) determines for each component in the product (1) whether it should be discarded or repaired upon failure and (2) at which echelon in the r...
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Given a product design and a repair network, a level of repair analysis (LORA) determines for each component in the product (1) whether it should be discarded or repaired upon failure and (2) at which echelon in the repair network to do this. The objective of the LORA is to minimize the total (variable and fixed) costs. We propose an IP model that generalizes the existing models, based on cases that we have seen in practice. Analysis of our model reveals that the integrality constraints on a large number of binary variables can be relaxed without yielding a fractional solution. As a result, we are able to solve problem instances of a realistic size in a couple of seconds on average. Furthermore, we suggest some improvements to the LORA analysis in the current literature.
While there exist clear methods for validating and ensuring the quality of solutions generated by forest planning heuristic techniques, the use of these methods in the literature varies from one situation to the next....
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While there exist clear methods for validating and ensuring the quality of solutions generated by forest planning heuristic techniques, the use of these methods in the literature varies from one situation to the next. Based on our experience developing and using heuristic forest planning techniques, we describe six levels of heuristic validation that are currently in use, ranging from no validation (Level 1) on one end of the spectrum, to the comparison of heuristic technique solutions with an exact solution obtained using mathematical programming methods (Level 6) on the other end. The reasons why authors may choose or reviewers may require levels of validation are proposed. We do not believe that all research papers should be subjected to the highest level of validation, but suggest that authors of papers on forest planning techniques and reviewers associated with peer-reviewed journals try to place the level of validation within the larger scientific context, then determine an appropriate level of validation. Admittedly, this is problematic for review decisions, given the fact that reviewers may differ in opinion of what is appropriate. Four brief cases are provided to help one think through these issues. Ultimately, we hope that this discussion will lead to a reasoned approach for the use of validation processes in conjunction with the presentation of heuristic techniques, rather than the current ad-hoc process that, on one hand, relies on the valuable and careful thoughts of the reviewers, yet on the other hand, may be uneven in application.
Design and management of logistic networks is one of the most critical issues in supply chain management. However, the literature does not contain any effective models, methods, and applications that simultaneously su...
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Design and management of logistic networks is one of the most critical issues in supply chain management. However, the literature does not contain any effective models, methods, and applications that simultaneously support management decisions in the strategic design of the distribution system, in the operational planning and organization of vehicles, and in container trips organization adopting different modes of transportation. The aim of this paper is to illustrate an original framework for the design and optimization of a multi echelon and multi level production/distribution system that combines mixed-integer linear programming modeling with cluster analysis, heuristic algorithms, and optimal transportation rules. A significant case study is illustrated revealing the effectiveness of the approach and tools proposed. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.
For many decades, solving the optimal architectural layout design is unattainable for the reasonable problem sizes. Architects have to settle foil acceptable layouts instead of the favourable optimal solution. With to...
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ISBN:
(纸本)1402034601
For many decades, solving the optimal architectural layout design is unattainable for the reasonable problem sizes. Architects have to settle foil acceptable layouts instead of the favourable optimal solution. With today technologies, various optimization techniques have been used to alleviate the optimal search according to diversified goals. This paper formulates the optimal architectural layout design as the multiobjective mixed integer programming model solved by the MIP solver. The main idea is to capture functional constraints, dimensional constraints and the objective function using only linear formulae with binary variables. Functional constraints are the connectivities, the unused grid cells, the fixed room location, the boundary and the fixed border location while dimension constraints are the non-intersecting, the overlapping, the length and the ratio constraints. The objective function is designed to minimize the absolute distance among rooms and maximize room spaces. Due to the nonlinearity of area computation, the linear approximation of width and height constraints have been utilized. Architects can control these different objectives within the model. By specifying the rigid restriction and the time limits, the problem can be solved within a reasonable amount of time.
Asset assignment and scheduling algorithms were developed and implemented to support a team-in-the-loop planning experiment conducted at the Naval Postgraduate School (NPS) in March 2009. The experiment examined plann...
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ISBN:
(纸本)9781424427932
Asset assignment and scheduling algorithms were developed and implemented to support a team-in-the-loop planning experiment conducted at the Naval Postgraduate School (NPS) in March 2009. The experiment examined planning and information flows among three cells in an abstracted and simplified Maritime Operations Center (MOC). This paper describes two optimization-based modules that focused on the Future Operations (FOPS) cell's planning activities. Module 1, a FOPS Planning Module, was a decision aid that presented the planners with N-best asset packages that would meet individual task requirements, while maximizing task execution accuracy. Module 2, a Scheduling Module, was an optimization-based scheduling algorithm that was used by experiment designers to set the conditions for the mission planning activity (e.g., asset types and numbers, task requirements and asset capabilities), and to assure that the tasks presented to the human planners would be achievable to a specified level of accuracy. A third module, termed Current Operations (COPS) Risk Analysis module, not discussed in detail here, was also implemented to assist COPS players on the consequences of redirecting assets from an ongoing task.
This paper designs a mixed algorithm called PSO_ACS to solve the vehicle routing problem with simultaneous pick-up and delivery. The ACS and PSO are combined by defining Information heuristic factor and expectation he...
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ISBN:
(纸本)9781424447053
This paper designs a mixed algorithm called PSO_ACS to solve the vehicle routing problem with simultaneous pick-up and delivery. The ACS and PSO are combined by defining Information heuristic factor and expectation heuristic factor as the functions of the particle's positions, and the PSO algorithm is adopted to improve the heuristics parameters self-adaptively. This algorithm improves the convergent speed through changing the inertial weight of the PSO. The remits of the numerical experiments on the Dethloff instances show that the mixed algorithm could get better value in efficient time.
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