Showing papers on "Heuristic (computer science) published in 1990"

The R*-tree: an efficient and robust access method for points and rectangles

Abstract: The R-tree, one of the most popular access methods for rectangles, is based on the heuristic optimization of the area of the enclosing rectangle in each inner node. By running numerous experiments ...

Why functional programming matters

Abstract: As software becomes more and more complex, it is more and more important to structure it well. Well-structured software is easy to write and to debug, and provides a collection of modules that can be reused to reduce future programming costs. In this paper we show that two features of functional languages in particular, higher-order functions and lazy evaluation, can contribute significantly to modularity. As examples, we manipulate lists and trees, program several numerical algorithms, and implement the alpha-beta heuristic (an algorithm from Artificial Intelligence used in game-playing programs). We conclude that since modularity is the key to successful programming, functional programming oers important advantages for software development.

Split delivery routing

Abstract: This article examines a relaxed version of the generic vehicle routing problem. In this version, a delivery to a demand point can be split between any number of vehicles. In spite of this relaxation the problem remains computationally hard. Since only small instances of the vehicle routing problem are known to be solved using exact methods, the vehicle route construction for this problem version is approached using heuristic rules. The main contribution of this article to the existing body of literature on vehicle routing issues in (a) is presenting a new vehicle routing problem amenable to practical applications, and (b) demonstrating the potential for cost savings over similar “traditional” vehicle routing when implementing the model and solutions presented here. The solution scheme allowing for split deliveries is compared with a solution in which no split deliveries are allowed. The comparison is conducted on six sets of 30 problems each for problems of size 75, 115, and 150 demand points (all together 540 problems). For very small demands (up to 10% of vehicle's capacity) no significant difference in solutions is evident for both solution schemes. For the other five problem sets for which point demand exceeds 10% of vehicle's capacity, very significant cost savings are realized when allowing split deliveries. The savings are significant both in the total distance and the number of vehicles required. The vehicles' routes constructed by our procedure tend to cover cohesive geographical zones and retain some properties of optimal solutions.

An efficient heuristic in manufacturing cell formation for group technology applications

Abstract: SUMMARY In this paper, the problem of obtaining a good decomposition of the manufacturing system into manufacturing cells is addressed. The parts can be partitioned into families, whereby each part family is assigned to a single cell. A simple twofold heuristic algorithm capable of minimizing inter-cell material movement, and addressing industrial applications of realistic dimensions is presented. The first step of the proposed heuristic is a bottom-up aggregation procedure to minimize what is defined as 'Normalized Inter-Cell Traffic'. The second step is a procedure to attempt further improvement, in which the significance of a machine to a cell is validated. A large scale industrial application of the system is also presented.

Sensitivity analysis based heuristic algorithms for mathematical programs with variational inequality constraints

Abstract: In this paper we consider heuristic algorithms for a special case of the generalized bilevel mathematical programming problem in which one of the levels is represented as a variational inequality problem. Such problems arise in network design and economic planning. We obtain derivative information needed to implement these algorithms for such bilevel problems from the theory of sensitivity analysis for variational inequalities. We provide computational results for several numerical examples.

The tabu search metaheuristic: How we used it

Abstract: A general description of tabu search is given and various applications to optimization problems are presented. Some guidelines for applying the tabu metaheuristic are exhibited.

On the multiple-query optimization problem

Abstract: The complexity of the multiple-query optimization problem in database management systems is examined. It is shown that the problem is NP-hard. Then the authors examine the performance of a heuristic algorithm to solve the multiple-query optimization problem and suggest some heuristics for query ordering which improve the efficiency of the algorithm considerably. Some experimental results on the performance of various heuristics are also presented. >

A graph partitioning procedure for machine assignment and cell formation in group technology

Abstract: SUMMARY This paper proposes a mathematical model and solution procedure for the group technology configuration problem—the grouping of individual machines into cells and the routing of components to machines within cells. Costs of inventory, machine depreciation, machine setup and material handling are first incorporated into a mathematical programming formulation. The formulation is then divided into two subproblems to facilitate solution. A heuristic graph partitioning procedure is then proposed for each subproblem. The first subproblem assigns components to specific machines. The second subproblem groups machines into cells. An approach for determining economic batch sizes in this environment is also included. Examples are included and the flexibility of the approach to various environments is discussed.

Artificial intelligence, heuristic frameworks and tabu search

Abstract: This paper examines some of the characteristics of AI-based heuristic procedures that have emerged as frameworks for solving difficult optimization problems. Consideration of attributes shared to some degree by human problem solvers leads to focusing in greater detail on one of the more successful procedures, tabu search, which employs a flexible memory system (in contrast to “memoryless” systems, as in simulated annealing and genetic algorithms, and rigid memory systems as in branch and bound and A* search). Specific attention is given to the short-term memory component of tabu search, which has provided solutions superior to the best obtained by other methods for a variety of problems. Our development emphasizes the principles underlying the interplay between restricting the search to avoid unproductive retracing of paths (by means of tabu conditions) and freeing the search to explore otherwise forbidden avenues (by aspiration criteria). Finally, we discuss briefly the relevance of a supplementary framework, called target analysis, which is a method for determining good decision rules to enable heuristics to perform more effectively.

Newton's method for the nonlinear complementarity problem: a B-differentiable equation problem

Abstract: This paper describes a damped-Newton method for solving the nonlinear complementarity problem when it is formulated as a system of B-differentiable equations through the use of the Minty-map. This general Newton algorithm contains a one-dimensional line search and possesses a global convergence property under certain conditions; modifications and heuristic implementations of the algorithm for the case when these conditions do not hold are also discussed. The numerical experiments show that, in general, this new scheme is more efficient and robust than the traditional Josephy-Newton algorithm.

Backbone Network Design Tools with Economic Tradeoffs

Abstract: This paper studies the problem of assigning capacities to the links in a backbone network and determining the primary routes used by messages for each origin-destination communicating pair in the network. The topology of the backbone network is assumed to be known and the end to end traffic requirements are given. The problem is to find the least cost design where the system costs are composed of connection costs which depend on link capacities and queueing costs which are incurred by users due to the limited capacities of links. The goal is to determine the routing and link capacities simultaneously. The problem is formulated and lower bounds are obtained by Lagrangean relaxation embedded in a subgradient optimization procedure. Cut constraints which are redundant in the original formulation are introduced, they improve the lower bounds. A heuristic method based on the Lagrangean solution is described. Extensive computational results are reported. INFORMS Journal on Computing, ISSN 1091-9856, was publish...

Minimizing path delay in a machine by compensation of timing through selective placement and partitioning

Abstract: A method for minimizing cycle time to improve machine performance is described. The approach prioritizes placement and partitioning decisions based on the criticality of paths and their constituent net segments. It provides an initial coarse approximation to a final more optimum configuration by iteratively improving on it through the use of deterministic techniques. The method optimizes placement by means of heuristic algorithms that are based on a cost function that is dependent on net segment and path criticality.

Congestion-driven placement using a new multi-partitioning heuristic

Abstract: A novel hierarchical top down placement technique is presented for circuits implemented in the sea-of-gates design style. It is based on a new hypergraph multi-partitioning algorithm, whose time complexity is linear in the number of pins of a circuit. The partitioning algorithm uses Steiner tress for the modeling of net topologies, which allows taking wiring congestion into account during placement. This leads to a more sophisticated balance criterion compared to conventional min-cut algorithms and consequently to a better distribution of active elements and wiring over the chip area. Experimental results show that the application of the new method makes the wiring of designs considerably easier. >

Routing in Point-to-Point Delivery Systems: Formulations and Solution Heuristics

Abstract: We develop an optimization-based approach for a point-to-point route planning problem that arises in many large scale delivery systems (for example, less-than-truckload freight, rail, mail and package delivery, communications) In these settings, a firm which must ship goods between many origin and destination pairs on a network needs to specify a route for each origin–destination pair so as to minimize transportation costs and/or transit times Typically, the cost structure is very complicated The approach discussed in this paper exploits the structure of the problem to decompose it into two smaller subproblems, each amenable to solution by a combination of optimization and heuristic techniques One subproblem is an “assignment” problem with capacity constraints The other subproblem is a mixed-integer multicommodity flow problem We propose solution methods based on Lagrangian relaxation for each subproblem Computational results with these methods and with a heuristic procedure for the multicommodity

Stochastic evolution: a fast effective heuristic for some generic layout problems

Abstract: There are two canonical optimization problems, namely, NETWORK BISECTIONING (NB) and TRAVELING SALESMAN (TS), that emerge from the physical design and layout of integrated circuits. In this paper, we use an analogy between iterative techniques for combinatorial optimization and the evolution of biological species to obtain the Stochastic Evolution (SE) heuristic for solving a wide range of combinatorial optimization problems. We show that SE can be specifically tailored to solve both NB and TS. Experimental results for the NB and TS problems show that the SE algorithm produces better quality solutions and is faster than the Simulated Annealing algorithm in all instances considered.

Technique for producing an expert system for system fault diagnosis

Abstract: The present invention relates to a technique for operation on a computer for developing the knowledge base for ultimately providing very fast and cost-efficient fault diagnosis systems. The present technique uses an effective hierarchy of rules where at a first level are rules which allow the arrangement of the system under test to be decomposed into a hierachy of sequential and parallel subsystems. At the second level are rules that generate the efficient testing rules for each pure subsystem. The second level rules can be compared to a node evaluation function in a typical problem of searching a graph to select the best node for expansion from a current list of candidate nodes, so that the best path to the correct system diagnosis is found in the shortest amount of time using a minimum of user input. Two heuristic rules are applied to speed-up the process of selecting the node as the best candidate for expansion. The resultant hierarchy of rules permit the cost-efficient knowledge base and resultant output test tree procedure to be generated for a fault diagnosis system to be applied for testing an associated device or system.

Automatic sensor and light source positioning for machine vision

Abstract: The authors discuss an optimization approach to automatic sensor and light source positioning for a machine vision task where geometric measurement and/or object verification is important. The goal of the vision task is assumed to be specified in terms of edge visibility. There are two types of edge visibility: geometric edge visibility tells how much of the given edge is not occluded, and photometric visibility tells how much of the given edge has enough contrast to be detected in the image. A heuristic optimality criterion for the optimal sensor and light source position is defined in terms of these two edge visibilities. A preliminary experiment has been conducted to demonstrate the feasibility of the optimization approach. The result shows that the optimization problem formulated can be solved by mathematical programming techniques. >

The synthesis of cost optimal heat exchanger networks: An industrial review of the state of the art

Abstract: The industrial heat exchanger network synthesis (HENS) problem is very complex and involves combinatorial problems in the “matching” between hot and cold streams to enhance heat recovery, temperature dependent physical and transport properties, the choice of flow configuration and materials of construction for the heat exchangers, the combination of “hard” and “soft” problem data (some target temperatures must be met, while others may be varied within limits if this is of advantage for the total process economy), various kinds of constraints (forbidden and compulsory matches) and different types of streams (liquid, vapour and mixed phase). Pressure drop limitations and the cost of piping are also important. The design objective includes a quantitative part (cost of heat exchange equipment and external utilities) and a qualitative part (safety, operability, flexibility and controllability). This makes it difficult to establish a single objective function to evaluate the design. Due to topological effects (services are added or removed), the investment cost function exhibits discontinuities since there is a unit cost involved in the equipment. Some of the qualitative aspects mentioned above cannot easily be formulated ahead of time. The cost of flexibility can be calculated, but only for given situations (networks). The global optimum is thus hard to guarantee and the engineer has to resort to simplifications of the model and some heuristic rules that will lead towards a near optimal solution. Research is progressing along three different lines which are the use of thermodynamic concepts, mathematical methods and the use of knowledge based systems for process design. In order to solve real life industrial problems, the engineer should take advantage of all these disciplines. However, the skill and experience of the engineer himself will remain of vital importance. This paper presents the state of the art of HENS methods together with some applications to previous literature problems. An evaluation of the various methods is performed from an industrial point of view. There is also a brief discussion of some of the software tools available to solve such problems. The presentation will emphasize on the design of the heat exchanger network itself although interactions with the rest of the process and the utility system inevitably will be discussed. The aspects of flexibility and operability will also be briefly mentioned. HENS is the most mature field of process synthesis when it comes to systematic methods. The increase of energy prices during the 70s and early 80s has been the major driving force. As things have been developed, however, the emphasis has changed from energy optimal (minimal) structures to cost optimal networks. The latest developed methods can find the proper trade-off between investment cost and operating cost for any price scenario (including regional factors such as the cooling water temperature etc.) ahead of design. Nevertheless, all problems have not yet been solved, and important research is still being conducted addressing all three areas of HENS, which are targeting, synthesis and optimization. Industry spends a significant amount of money to carry out energy analysis of new and existing plants, to support academia in their research and to develop and acquire accurate and efficient computer tools. It is the involvement of our company in these areas that has given us the opportunity, on an industrial basis, to review the field. In the past there have been two schools of HENS. One relies on thermodynamic principles and a few heuristic rules, where the designer manually (or interactively if software is available) synthesizes the network. The other, more automatic, approach relies on mathematical methods like linear and nonlinear programming. The relative merits of these schools will be discussed with reference to case studies. There will also be a short presentation of the historical development within these schools.

Analysis of Christofides' heuristic: some paths are more difficult than cycles

Abstract: For the traveling salesman problem in which the distances satisfy the triangle inequality, Christofides' heuristic produces a tour whose length is guaranteed to be less than 32 times the optimum tour length. We investigate the performance of appropriate modifications of this heuristic for the problem of finding a shortest Hamiltonian path. There are three variants of this problem, depending on the number of prespecified endpoints: zero, one, or two. It is not hard to see that, for the first two problems, the worst-case performance ratio of a Christofides-like heuristic is still 32. For the third case, we show that the ratio is 53 and that this bound is tight.

Geometric Approaches to Solve the Chebyshev Traveling Salesman Problem

Abstract: Several heuristic procedures based on geometric concepts have been developed for the Chebyshev (or too) Traveling Salesman Problem (CTSP),which has numerous applications in materials handling and information storage-retrieval. The following study is concerned with evaluating the performance of geometric approaches as a function of the shape of the service region and the number of points to be sequenced. A new approach, the band insertion heuristic, is also introduced and compared with existing procedures. Trade-offs in tour quality and solution effort are the primary focus of the study, which is empirical in nature; however, the results generally apply to a wide range of configurations.

Delay and area optimization in standard-cell design

Abstract: A heuristic approach to the optimal selection of standard cells in VLSI circuit design is presented. A cell library is composed of several templates (3-5) for each type of cell. These templates differ in area, driving capabilities, intrinsic delay, and capacitive loading. When realizing a logically synthesized circuit, one selects the best templates from the cell library to minimize the total area of the cells under delay constraints. The algorithm is capable of handling efficiently relatively large designs taking into account the entire circuit, not iterating on a path basis. Carefully chosen weights reflect the significance of particular cells in the circuit and guide the template selection process. Because the algorithm is capable of increasing and decreasing the templates, very good experimental results are achieved. >

A new global router based on a flow model and linear assignment

Abstract: A novel heuristic for global routing in graphs is developed. Based on a flow model it can handle many nets simultaneously, thus reducing the net ordering problem. To demonstrate the validity of the method it was applied to standard cell design style. For this application the authors combined the flow model approach with linear assignment to achieve a hierarchical global routing scheme. This procedure is about six times faster than the old flat net by net global router, while producing denser layouts for the majority of testcases. Good quality was achieved in comparison with the TimberwolfSC version 5.4 global router. >