This paper studies the problem of designing a logical topology over a wavelength-routed all-optical network (AON) physical topology, The physical topology consists of the nodes and fiber links in the network, On an AO...
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This paper studies the problem of designing a logical topology over a wavelength-routed all-optical network (AON) physical topology, The physical topology consists of the nodes and fiber links in the network, On an AON physical topology, we can set up lightpaths between pairs of nodes, where a lightpath represents a direct optical connection without any intermediate electronics, The set of lightpaths along with the nodes constitutes the logical topology, For a given network physical topology and traffic pattern (relative traffic distribution among the source-destination pairs), our objective is to design the logical topology and the routing algorithm on that topology so as to minimize the network congestion while constraining the average delay seen by a source-destination pair and the amount of processing required at the nodes (degree of the logical topology), We will see that ignoring the delay constraints can result in fairly convoluted logical topologies with very long delays, On the other hand, in all our examples, imposing it results in a minimal increase in congestion, While the number of wavelengths required to imbed the resulting logical topology on the physical all optical topology is also a constraint in general, we find that in many cases of interest this number can be quite small, We formulate the combined logical topology design and routing problem described above (ignoring the constraint on the number of available wavelengths) as a mixed integer linear programming problem which we then solve for a number of cases of a six-node network, Since this programming problem is computationally intractable for larger networks, we split it into two subproblems: logical topology design, which is computationally hard and will probably require heuristic algorithms, and routing, which can be solved by a linear program, We then compare the performance of several heuristic topology design algorithms (that do take wavelength assignment constraints into account) against
This paper presents a mixed integer linear programming (MILP) model for a new class of dynamic project selection and funding problems under risk given multiple scarce resources of different qualifications. The underly...
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This paper presents a mixed integer linear programming (MILP) model for a new class of dynamic project selection and funding problems under risk given multiple scarce resources of different qualifications. The underlying stochastic decision tree concept extends classical approaches mainly in that it adds a novel node type that allows for the continuous control of discrete branching probability distributions. The control functions are piecewise linear and are convex for the costs and concave for the benefits. The MILP-model has been embedded in a prototype Decision Support System (DSS). With respect to the proposed solution the DSS provides complete probability distributions for both costs and benefits.
This paper proposes fast FIR digital filter structures using the minimal number of adders. Filter coefficients are expressed with canonic signed digit (CSD) code and Hartley's technique is used to minimize the num...
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This paper proposes fast FIR digital filter structures using the minimal number of adders. Filter coefficients are expressed with canonic signed digit (CSD) code and Hartley's technique is used to minimize the number of adders and subtractors. The proposed filters implemented as wired logic are fast because the structure having the shortest critical path is selected. An algorithm is given to obtain such fast structures. In many examples the critical path length of the filter structures obtained using the proposed method is equal to that of the conventional CSD structures. This paper also presents a new design method of FIR filters using MILP. Utilization of common expressions in Hartley's technique widen the CSD coefficient space. Thus the mixed integer linear programming (MILP) may lead to better frequency responses. Superior frequency responses are actually obtained in many simulations.
This paper investigates the scaling properties of neural networks for solving job-shop scheduling problems. Specifically, the Tank-Hopfield linearprogramming network is modified to solve mixedintegerlinear programm...
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This paper investigates the scaling properties of neural networks for solving job-shop scheduling problems. Specifically, the Tank-Hopfield linearprogramming network is modified to solve mixed integer linear programming with the addition of step-function amplifiers. Using a linear energy function, our approach avoids the traditional problems associated with most Hopfield networks using quadratic energy functions. Although our approach requires more hardware (in terms of processing elements and resistive interconnects) than a recent approach by Zhou et al. [2], the neurons in the modified Tank-Hopfieid network do not perform extensive calculations unlike those described by Zhou et al.
A mixedintegerprogramming model is constructed for the operation of a single water supply reservoir during drought and impending drought. Operating on a critical sequence of low flows, the model determines trigger v...
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A mixedintegerprogramming model is constructed for the operation of a single water supply reservoir during drought and impending drought. Operating on a critical sequence of low flows, the model determines trigger volumes of storage plus anticipated inflow which signal the need for each of the several phases of rationing. The trigger volumes are examined as the allowed frequency of the various phases of rationing are varied.
This paper introduces a grey integerprogramming (GIP) method for facility expansion planning under uncertainty, by incorporating the concepts of grey number and grey mathematical programming into a mixedinteger line...
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This paper introduces a grey integerprogramming (GIP) method for facility expansion planning under uncertainty, by incorporating the concepts of grey number and grey mathematical programming into a mixed integer linear programming optimization framework. The approach is an improvement upon previous integerprogramming methods in terms of its technical characteristics and applicability. It allows uncertain information to be effectively communicated into the optimization process and the resulting solutions. It also has low computational requirements and is thus applicable to practical problems. The modelling approach is applied to a hypothetical planning problem of waste flow allocation and treatment/disposal facility expansion within a regional solid waste management system. The binary variable solutions provide the ranges of different development alternatives within a multi-period, multi-facility and multi-scale context, and the continuous variable solutions provide optimal schemes for waste flow allocation corresponding to the upper and lower bounds of the objective function value. The results indicate that reasonable and useful solutions can be achieved through the developed approach.
Though circumscription was introduced by McCarthy over a decade ago, there has been relatively little work on algorithms for computing circumscriptive databases. In this paper, we develop algorithms to compute the pre...
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Though circumscription was introduced by McCarthy over a decade ago, there has been relatively little work on algorithms for computing circumscriptive databases. In this paper, we develop algorithms to compute the preferred models of circumscriptive databases at compile-time using mixed integer linear programming techniques. Two advantages of this (bottom-up) approach are that it makes efficient re-use of previous computations and it provides much faster run-time performance. Some other advantages of using linearprogramming to automate deduction at compile time are that its re-optimization facilities elegantly accommodate database updates and also that it leads to a completely declarative formulation in which ordering of rules and literals in rule bodies plays no real role. Finally, we plan to use a standard relational database system as our run-time environment;this should yield relatively fast run-time processing, and provide a more expressive query language in which aggregates and the like can be expressed easily. (C) 1995 Academic Press. Inc.
The batch processing manufacturing environment is subject to a high degree of uncertainty. One of the key issues in producing practical process schedules in such an unfavourable environment is the assessment of their ...
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The batch processing manufacturing environment is subject to a high degree of uncertainty. One of the key issues in producing practical process schedules in such an unfavourable environment is the assessment of their robustness under uncertainty. This paper shows how Monte-Carlo based simulation models, implemented within the framework of the BATCHES simulator, can be used for this purpose, starting with the automated implementation of a given schedule into the simulation models, then running the various replicates of the simulation acid finally analysing their results. In addition, the possibility of feeding back the simulation results to the scheduling model is also discussed, paving the way towards the development of a more effective reactive scheduling system.
This paper describes the mathematical formulation, algorithm and some sample results of the advanced short-term hydroelectric generation scheduling function that has been developed as part of a new energy management s...
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This paper describes the mathematical formulation, algorithm and some sample results of the advanced short-term hydroelectric generation scheduling function that has been developed as part of a new energy management system. An approach to consider nonlinear, noncontinuous constraints in linear optimization problems, is presented in this paper. The hydroelectric generation and interchange is scheduled to maximize the profit from buying and selling energy while meeting these hydro operating constraints. This problem has been successfully solved for up to a 168 hour time frame using mixed integer linear programming (MILP). This method is well suited to solving this optimization problem with the complete set of hydro constraints, including the flow dependent ramp limits. This paper includes some details of results obtained for some actual operational scenarios, where it can be clearly demonstrated that the new algorithm produces hydro and interchange schedules which maximize the generation over the heavy load hours (in which the energy can be sold at a higher price) and minimize generation over the light load hours while meeting all constraints on the hydro system.
Many techniques have been proposed to optimize digital system timing. Each technique can be advantageous in particular applications, however they are most often applied individually rather than concurrently. The frame...
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Many techniques have been proposed to optimize digital system timing. Each technique can be advantageous in particular applications, however they are most often applied individually rather than concurrently. The framework presented here allows for concurrent timing optimization using retiming, intentional clock skew, and wave pipelining for latch-based designed systems with single or multi-phase clocking. This optimization is formulated as a mixedintegerlinear program. Our integrated framework also includes a new optimization technique called resynchronization which allows for the insertion of latches in the shortest paths and thus avoids race conditions. Our work has been applied to several designs and is able to significantly reduce the clock period.
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