Showing papers on "Heuristic published in 1987"

Dynamic Programming Approach to Unit Commitment

Abstract: A field-proven dynamic programming formulation of the unit commitment problem is presented. This approach features the classification of generating units into related groups so as to minimize the number of unit combinations which must be tested without precluding the optimal path. Programming techniques are described which maximize efficiency. Considerations are discussed which determine when generating units must be evaluated and when they may be ignored. The heuristic procedures described in this paper are concerned with supplying all apriori information to the program thereby minimizing its execution time. Results are presented from field testing on a medium size utility. Composite generating unit formulation is described for the economic allocation of constrained fuel to a group of units.

A within-cell utilization based heuristic for designing cellular manufacturing systems

Abstract: The initial stage in the facilities design of cellular manufacturing systems involves the identification of part families and machine groups and forming cells possessing specific manufacturing capabilities. A new heuristic for the part family/machine group formation (PF/MGF) problem is presented in this paper. The distinguishing feature of this heuristic is its consideration of several practical criteria such as within-cell machine utilization, work load fractions, maximum number of machines that are assigned to a cell, and the percentage of operations of parts completed within a single cell. Computational results, based on several examples from the literature, show that this heuristic performs well with respect to more than one criteria. The heuristic also clarifies the source of various arguments in the literature concerning the ‘goodness’ of the solutions obtained by other researchers. An application of the heuristic to a large sample of industrial data involving 45 workcentres composed of 64 machines,...

Scheduling Tasks with Resource Requirements in Hard Real-Time Systems

Abstract: This paper describes a heuristic approach for solving the problem of dynamically scheduling tasks in a real-time system where tasks have deadlines and general resource requirements. The crux of our approach lies in the heuristic function used to select the task to be scheduled next. The heuristic function is composed of three weighted factors. These factors explicitly consider information about real-time constraints of tasks and their utilization of resources. Simulation studies show that the weights for the various factors in the heuristic function have to be fine-tuned in order to obtain a degree of success in the range of 75-88 percent of that obtained via exhaustive search. However, modifying the approach to use limited backtracking improves the degree of success substantially to as high as 99.5 percent. This improvement is observed even when the initial set of weights are not tailored for a particular set of tasks. Simulation studies also show that in most cases the schedule determined by the heuristic algorithm is optimal or close to optimal.

A cost-based heuristic for group technology configuration†

Abstract: Group technology is a management philosophy capable of jointly simplifying management control and improving productivity. This paper proposes a heuristic approach to the economic determination of machine groups and their corresponding component families for group technology. The procedure considers costs of work-in-process and cycle inventory, intra-group material handling, set-up, variable processing and fixed machine costs. The three stage procedure initially reorders part types based on routing similarity. An attempt is then made to combine adjacent part types to reduce machine requirements. Finally groups are combined where economic benefits of utilization offset those of set-up, work-in-process and material handling. Examples illustrating the procedure and potential savings are included.

Quasiconvexity and Partial Regularity in the Calculus of Variations

Abstract: This note is a brief and mostly heuristic explanation of some of the main ideas in my recent paper [6], concerning the partial regularity of minimizers for certain natural problems in the calculus of variations.

Resolving adversarial conflicts: an approach integration case-based and analytic methods

Abstract: This thesis addresses the problem of finding compromise solutions to multi-agent conflicts. This is a difficult problem since the compromise choices that a problem solver has for continuum-valued goals are infinite, and the agents need to be persuaded to partially abandon goals during problem solving. To deal with these difficulties, we propose an integration of: (1) Heuristic Methods. Use of past cases similar to the current problem; (2) Analytic Methods. Application of multi-attribute utility theory to many decision makers. Past problem solving episodes similar to the current one are used to focus on the relevant parts of a problem, form a basis for analogical reasoning, avoid past mistakes, and suggest argumentation strategies. Utility theory is used to identify feasible compromises, evaluate whether a contemplated solution is an improvement on a previously rejected one and provide a computational formalism for persuasive argumentation. We present the processes mentioned above and the knowledge sources that support them. Our examples are taken from the domain of labor mediation and are implemented in a computer program, called the PERSUADER that functions as a mediator in hypothetical labor negotiations. Using the methods described, it suggests appropriate settlements to the disputants. If a suggested compromise is rejected, the PERSUADER attempts to either modify the settlement or the opposing party's "view" of the settlement using the same methods.

Heuristic solution methods for two location problems with unreliable facilities

Abstract: In this paper, the p-median and p-centre problems are generalized by considering the possibility that one or more of the facilities may become inactive. The unreliable p-median problem is defined by introducing the probability that a facility becomes inactive. The (p, q)-centre problem is defined when p facilities need to be located but up to q of them may become unavailable at the same time. An heuristic procedure is presented for each problem. A rigorous procedure is discussed for the (p, q)-centre problem. Computational results are presented.

A Heuristic Approach to Product Design

Abstract: A dynamic-programming heuristic is described to find approximate solutions to the problem of identifying a new, multi-attribute product profile associated with the highest share-of-choices in a competitive market. The input data consist of idiosyncratic multi-attribute preference functions estimated using conjoint or hybrid-conjoint analysis. An individual is assumed to choose a new product profile if he/she associates a higher utility with it than with a status-quo alternative. Importance weights are assigned to individuals to account for differences in their purchase and/or usage rates and the performance of a new product profile is evaluated after taking into account its cannibalization of a seller's existing brands. In a simulation with real-sized problems, the proposed heuristic strictly dominates an alternative lagrangian-relaxation heuristic in terms of both computational time and approximation of the optimal solution. Across 192 simulated problems, the dynamic-programming heuristic identifies product profiles whose share-of-choices, on average, are 98.2% of the share-of-choices of the optimal product profile, suggesting that it closely approximates the optimal solution.

Nearest-Neighbor Mapping of Finite Element Graphs onto Processor Meshes

Abstract: The processor allocation problem is addressed in the context of the parallelization of a finite element modeling program on a processor mesh. A heuristic two-step, graph-based mapping scheme with polynomial-time complexity is developed: 1) initial generation of a graph partition for nearest-neighbor mapping of the finite element graph onto the processor graph, and, 2) a heuristic boundary refinement procedure to incrementally alter the initial partition for improved load balancing among the processors. The effectiveness of the approach is gaged both by estimation using a model with empirically determined parameters, as well as implementation and experimental measurement on a 16 node hypercube parallel computer.

Preemptive Scheduling Under Time and Resource Constraints

Abstract: We consider the problem of scheduling a set of n preemptable tasks in a system having r resources. Each task has an arbitrary, but known, worst case processing time and a deadline, and may request simultaneous use of a number of resources. A resource can be used either in shared mode or exclusive mode. In this paper, we develop and evaluate algorithms for determining whether or not a set of preemptive tasks is schedulable in such a real-time system, and if so, determining a schedule for it. This scheduling problem is known to be computationally intensive. In many real-time application environments, tasks are scheduled dynamically, and hence the scheduling algorithms used must have low run-time costs. To keep run-time costs low, we propose the use of suboptimal but practical algorithms that employ computationally simple heuristics. The computational complexity of our algorithms for scheduling n tasks in a system having r resources is O(rn2), which is very much lower than that of known optimal algorithms. We report on the results of simulation studies performed on such heuristic preemptive scheduling algorithms and the sensitivity of the performance of the algorithms with respect to various scheduling parameters. These studies show that due to the complexity of the problem, straightforward heuristics do not perform satisfactorily. However, an algorithm that uses combinations of such heuristics in conjunction with limited backtracks works very well.

Efficient Algorithms for Layer Assignment Problem

Abstract: The layer assignment problem for interconnect is the problem of determining which layers should be used for wiring the signal nets. The objective of the layer assignment problem in general is to minimize the number of vias required. Thus, it is also referred to as the via minimization problem. In a via minimization problem, if the topology of the given layout is fixed, the problem is referred to as a constrained via minimization (CVM) problem. On the other hand, if both the topology of the layout and the layer assignment are to be decided, it is referred to as an unconstrained via minimization (UVM) problem. In this paper, both the CVM and UVM problems are studied. For the CVM problems, efficient algorithms which can be easily modified to take extra constraints into consideration are proposed. Experimental results show that the proposed algorithms for the CVM problem are time efficient compared with existing algorithms and generate better (near-optimal) results. For the UVM problems, a new heuristic approach is presented which generates better results but takes longer computing time. In the CVM problem, some vias are "essential" to the given layout. That is, they have to be selected and cannot be replaced by other possible vias. An efficient algorithm for identifying essential vias is also presented and discussed in this paper.

Troubleshooting: when modeling is the trouble

Abstract: This paper shows how order of magnitude reasoning has been successfully used for troubleshooting complex analog circuits. The originality of this approach was to be able to remove the gap between the information required to apply a general theory of diagnosis and the limited information actually available. The expert's ability to detect a defect by reasoning about the significant changes in behavior it induces is extensively exploited here: as a kind of reasoning that justifies the qualitative modeling, as a heuristic that defmes a strategy and as a working hypothesis that makes clear the scope of this approach.

Exact and Approximate Solutions for the Gate Matrix Layout Problem

Abstract: We consider the gate matrix layout problem for VLSI circuits, which is known to be NP-complete. We present an efficient algorithm for determining whether two tracks suffice. For the general problem of minimizing the number of tracks (and, hence, the area) needed, we design an attractive dynamic programming formulation to guarantee optimality. We also investigate the performance of fast heuristic algorithms published in the literature and demonstrate that there exist families of problem instances for which the ratio of the number of tracks required by these heuristics to the optimal value is unbounded. Moreover, we show that this result holds for any on-line layout algorithm. We additionally prove that, unless P = NP, no polynomial-time layout algorithm can ensure that the number of tracks it requires never exceeds k plus the optimum, for any constant k.

The stochastic queue p-median problem

Abstract: This paper derives two easily programmable heuristic procedures for locating p mobile service units on a network in the presence of queueing-like congestion. Both heuristics take advantage of the Hypercube model, a location model for a single service unit, and a normalizing technique known as mean service time calibration. Heuristic 1 uses the 1-median problem, whereas heuristic 2 uses the stochastic queue median. A simulation model is employed to validate the results and compare the heuristics.

A layout design heuristic employing the theory of fuzzy sets

Abstract: This paper discusses various techniques for layout planning and outlines an application of fuzzy set techniques to the block layout design problem. In particular, a fuzzy linguistic heuristic for the location of the departments within a facility is proposed. This heuristic utilizes imprecise descriptors for two distinct design categories: closeness and importance, expressed in the form of fuzzy relations for every pair of departments. A numerical example is given to illustrate the proposed approach and directions for further research are discussed.

Real-time heuristic search: first results

Abstract: Existing heuristic search algorithms are not applicable to real-time applications because they cannot commit to a move before an entire solution is found. We present a special case of minimax lookahead search to handle this problem, and an analog of alpha-beta pruning that significantly improves the efficiency of the algorithm. In addition, we present a new algorithm, called R.ea1-Time-A *, for searching when actions must actually be executed, as opposed to merely simulated. Finally, we examine the nature of the tradeoff between computation and execution cost.

Connect-the-dots: a new heuristic

Abstract: The problem considered in this paper is that of finding a simple polygon through a given set of points in the plane that is “natural” in some perceptual sense. We propose that a particular geometric object called the minimal spanning Voronoi tree captures the essence of the problem. Despite the fact that we can neither prove the existence of this geometric object nor design an exact algorithm for finding it, a search heuristic results in remarkably pleasing solutions to the problem.

Large Tree Classifier with Heuristic Search and Global Training

Abstract: In the tree classifier with top-down search, a global decision is made via a series of local decisions. Although this approach gains in classification efficiency, it also gives rise to error accumulation which can be very harmful when the number of classes is very large. To overcome this difficulty, a new tree classifier with the following characteristics is proposed: 1) fuzzy logic search is used to find all ``possible correct classes,'' and some similarity measures are used to determine the ``most probable class''; 2) global training is applied to generate extended terminals in order to enhance the recognition rate; 3) both the training and search algorithms have been given a lot of flexibility, to provide tradeoffs between error and rejection rates, and between the recognition rate and speed. A computer simulation of the decision trees for the recognition of 3200 Chinese character categories yielded a very high recognition rate of 99.93 percent and a very high speed of 861 samples/s, when the program was written in a high level language and run on a large multiuser time-sharing computer.

Conference Seminar Timetabling

Abstract: Participants at a conference held in 1985 were asked to select seminars that they wished to attend, before the schedule of seminars was constructed The conference organizers were then faced with the problem of finding a timetable that would allow participants to attend the seminars they had chosen This interesting combinatorial optimization problem is investigated here A heuristic method, incorporating an annealing algorithm, is developed to help the organizers timetable similar conferences in the future

Time Slot Assignment in SS/TDMA Systems with Intersatellite Links

Abstract: In this paper we study the time slot assignment problem in clusters of SS/TDMA satellite systems interconnected through intersatellite links. We show that the problem of finding an assignment which minimizes the total transmission time is NP-complete, i.e., computationally intractable, even for quite restricted intersatellite link patterns and simplified system models. Successively, we focus our attention on clusters of two satellites, proposing a branch-and-bound optimal algorithm and two fast heuristic algorithms. We investigate the performance of the proposed heuristic algorithms both by a theoretical worst case bound and by simulation trials showing that the produced solutions are close to the optimal on the average.