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Showing papers on "Heuristic (computer science) published in 1989"


Journal ArticleDOI
TL;DR: In this paper, a Lagrangian relaxation of the capacity constraints of CLSP allows it to be decomposed into a set of uncapacitated single product lot sizing problems, which are solved by dynamic programming.
Abstract: This research focuses on the effect of setup time on lot sizing. The setting is the Capacitated Lot Sizing Problem (the single-machine lot sizing problem) with nonstationary costs, demands, and setup times. A Lagrangian relaxation of the capacity constraints of CLSP allows it to be decomposed into a set of uncapacitated single product lot sizing problems. The Lagrangian dual costs are updated by subgradient optimization, and the single-item problems are solved by dynamic programming. A heuristic smoothing procedure constructs feasible solutions (production plans) which do not require overtime. The algorithm solves problems with setup time or setup cost. Problems with extremely tightly binding capacity constraints were much more difficult to solve than anticipated. Solutions without overtime could not always be found for them. The most significant results are that (1) the tightness of the capacity constraint is a good indicator of problem difficulty for problems with setup time; and (2) the algorithm solve...

444 citations


Journal ArticleDOI
TL;DR: In this paper, a new heuristic method is presented for solving the m -machine, n -job flow shop scheduling problem, which is composed of two phases: the first finds an initial sequence using an analogy with the travelling salesman problem and the second tries to improve this solution using taboo search techniques.

350 citations


13 Apr 1989
TL;DR: In this article, the authors developed an efficient scheduling algorithm based on heuristic algorithms to schedule a set of TASKS on a multi-rocessor real-time system.
Abstract: HARD REAL-TIME SYSTEMS REQUIRE BOTH FUNCTIONALLY CORRECT EXECUTIONS AND RESULTS THAT ARE PRODUCED ON TIME. THIS MEANS THAT THE TASK SCHEDULING ALGORITHM IS AN IMPORTANT COMPONENT OF THESE SYSTEMS. IN THIS PAPER, EFFICIENT SCHEDULING ALGORITHMS BASED ON HEURISTIC FUNCTIONS ARE DEVELOPED TO SCHEDULE A SET OF TASKS ON A MULTIPROCESSOR SYSTEM. THE TASKS ARE CHARACTERIZED BY WORST CASE COMPUTATION TIMES, DEADLINES AND RESOURCES REQUIREMENTS. STARTING WITH AN EMPTY PARTIAL SCHEDULE, EACH STOP OF THE SEARCH EXTENDS THE CURRENT PARTIAL SCHEDULE WITH ONE OF THE TASKS YET TO BE SCHEDULED. THE HEURISTIC FUNCTIONS USED IN THE ALGORITHM ACTIVELY DIRECT THE SEARCH FOR A FEASIBLE SCHEDULE, I.E., THEY HELP CHOOSE `THE TASK'' THAT EXTENDS THE CURRENT PARTIAL SCHEDULE. TWO SCHEDULING ALGORITHMS ARE EVALUATED VIA SIMULATION. FOR EXTENDING THE CURRENT PARTIAL SCHEDULE, ONE OF THE ALGORITHMS CONSIDERS, AT EACH STEP OF THE SEARCH, `ALL'' THE TASKS THAT ARE YET TO BE SCHEDULED AS CANDIDATES. THE SECOND ALGORITHM IS SHOWN TO BE VERY EFFECTIVE WHEN THE MAXIMUM ALLOWABLE SCHEDUL- ING OVERHEAD IS FIXED. THIS ALGORITHM IS HENCE APPROPRIATE FOR DYNAMIC SCHEDULING IN REAL-TIME SYSTEMS.

339 citations


Journal ArticleDOI
TL;DR: This paper describes a cutting plane algorithm that is based on the simplex method and uses exact and heuristic separation routines for some of the classes of facets of the associated polytope.
Abstract: In this paper we consider a clustering problem that arises in qualitative data analysis. This problem can be transformed to a combinatorial optimization problem, the clique partitioning problem. We have studied the latter problem from a polyhedral point of view and determined large classes of facets of the associated polytope. These theoretical results are utilized in this paper. We describe a cutting plane algorithm that is based on the simplex method and uses exact and heuristic separation routines for some of the classes of facets mentioned before. We discuss some details of the implementation of our code and present our computational results. We mention applications from, e.g., zoology, economics, and the political sciences.

328 citations


Journal ArticleDOI
TL;DR: It is shown in particular that, given any desired product mix, it is possible to start the system with enough jobs in process so that some machines will be fully utilized in steady-state and the productivity is optimal.
Abstract: Timed event-graphs, a special class of timed Petri nets, are used for modelling and analyzing job-shop systems. The modelling allows the steady-state performance of the system to be evaluated under a deterministic and cyclic production process. Given any fixed processing times, the productivity (i.e., production rate) of the system can be determined from the initial state. It is shown in particular that, given any desired product mix, it is possible to start the system with enough jobs in process so that some machines will be fully utilized in steady-state. These machines are called bottleneck machines, since they limit the throughput of the system. In that case, the system works at the maximal rate and the productivity is optimal. The minimal number of jobs in process allowing optimal functioning of the system is further specified as an integer linear programming problem. An efficient heuristic algorithm is developed to obtain a near-optimal solution. >

318 citations


Journal ArticleDOI
TL;DR: Heuristic approaches to an assembly line with m stations in series having finite capacity buffers based on an equivalent maximum flow problem and on critical path techniques are proposed.
Abstract: We consider an assembly line with m stations in series having finite capacity buffers. Blocking occurs when buffers are full. There are M different types of products to be assembled, each with its own processing requirements. There is a production target set for each type. The problem is to operate the line to maximize throughput. We propose heuristic approaches to this problem based on an equivalent maximum flow problem and on critical path techniques.

316 citations


Journal ArticleDOI
TL;DR: This paper embeds the hypercube queueing model in a single node substitution heuristic optimization procedure, to determine a set of server locations which “maximize” the expected coverage, and discusses modifications and enhancements to the MEXCLP's heuristic solution procedure for this adjusted model.
Abstract: The Maximal Expected Coverage Location Problem (MEXCLP) addresses the problem of optimally locating servers so as to maximize the expected coverage of demand while taking into account the possibility of servers being unavailable when a call enters the service system. In this paper, an attempt is made to relax three of MEXCLP's assumptions: servers operate independently, servers have the same busy probabilities, and server busy probabilities are invariant with respect to their locations. We embed the hypercube queueing model in a single node substitution heuristic optimization procedure, to determine a set of server locations which “maximize” the expected coverage. Our empirical findings indicate that there is disagreement between the expected coverage predicted by the MEXCLP model and the hypercube optimization procedure. There is substantial agreement, however, between the locations generated by the two procedures. We also consider a simple “adjustment” to the MEXCLP model, based upon random sampling of ...

266 citations


Proceedings ArticleDOI
01 May 1989
TL;DR: Some heuristic channel-assignment algorithms for cellular systems are described, developed, in part, by suitably adapting some of the ideas previously introduced in heuristic graph-coloring algorithms.
Abstract: Some heuristic channel-assignment algorithms for cellular systems are described. These algorithms have yielded optimal, or near-optimal assignments, in many cases. The channel-assignment problem can be viewed as a generalized graph-coloring problem, and these algorithms have been developed, in part, by suitably adapting some of the ideas previously introduced in heuristic graph-coloring algorithms. The channel-assignment problem is formulated as a minimum-span problem, i.e. a problem wherein the requirement is to find the minimum bandwidth necessary to satisfy a given demand. Examples are presented, and algorithm performance results are discussed. >

242 citations


Journal ArticleDOI
TL;DR: This survey considers emerging approaches of heuristic search for solutions to combinatorially complex problems that arise in business applications, such as in manufacturing operations, financial investment, capital budgeting and resource management.

234 citations


Journal ArticleDOI
TL;DR: Simple heuristic formulas are developed to estimate the simulation run lengths required to achieve desired statistical precision in queueing simulations and apply to stochastic processes that can be approximated by reflected Brownian motion, such as the queue-length process in the standard GI/G/1 model.
Abstract: Simple heuristic formulas are developed to estimate the simulation run lengths required to achieve desired statistical precision in queueing simulations. The formulas are intended to help in the early planning stages before any data have been collected. The queueing simulations considered are single replications (one long run) conducted to estimate steady-state characteristics such as expected equilibrium queue lengths. The formulas can be applied to design simulation experiments to develop and evaluate queueing approximations. In fact, this work was motivated by efforts to develop approximations for packet communication networks with multiple classes of traffic having different service characteristics and bursty arrival processes. In addition to indicating the approximate simulation run length required in each case of a designed experiment, the formulas can help determine what cases to consider, what statistical precision to aim for, and even whether to conduct the experiment at all. The formulas are bas...

193 citations




Journal ArticleDOI
TL;DR: A fast and effective branch-and-bound algorithm, which incorporates this heuristic for use in bounding, is developed, which introduces heuristic fathoming as a technique for reducing the size of the branch- and-bound tree.
Abstract: A simple, fast and effective heuristic for the Simple Assembly Line Balancing Type I problem (minimizing the number of workstations) is proposed. A fast and effective branch-and-bound algorithm, which incorporates this heuristic for use in bounding, is developed. The algorithm introduces heuristic fathoming as a technique for reducing the size of the branch-and-bound tree. Methods to solve the Simple Assembly Line Balancing Type II problem (maximizing the production rate) are also described. Upper bounds on all heuristics for both problems are provided.

Proceedings ArticleDOI
21 Jun 1989
TL;DR: This paper presents a new coherent set of heuristic methods for reducing the amount of spill code generated, which results in more efficient (and shorter) compiled code.
Abstract: Global register allocation and spilling is commonly performed by solving a graph coloring problem. In this paper we present a new coherent set of heuristic methods for reducing the amount of spill code generated. This results in more efficient (and shorter) compiled code. Our approach has been compared to both standard and priority-based coloring algorithms, universally outperforming them.In our approach, we extend the capability of the existing algorithms in several ways. First, we use multiple heuristic functions to increase the likelihood that less spill code will be inserted. We have found three complementary heuristic functions which together appear to span a large proportion of good spill decisions. Second, we use a specially tuned greedy heuristic for determining the order of deleting (and hence coloring) the unconstrained vertices. Third, we have developed a “cleaning” technique which avoids some of the insertion of spill code in non-busy regions.

Journal ArticleDOI
TL;DR: In this article, the authors presented the formulation and solution of a combined train routing and makeup, and empty car distribution model, which results in a large scale mixed-integer programming problem with nonlinear objective function and linear constraints.
Abstract: This paper presents the formulation and solution of a combined train routing and makeup, and empty car distribution model. This formulation results in a large scale mixed-integer programming problem with nonlinear objective function and linear constraints. A heuristic decomposition technique is developed to solve the model. This solution procedure exploits the special structure of the problem and decomposes it into smaller subproblems based on the type of decision variables. Model testing results are also presented.

Journal ArticleDOI
01 Mar 1989-Networks
TL;DR: This work considers the problem of routing multiple commodities between various origin—destination pairs in a network, at minimum total cost, as a mixed-integer program and develops a composite algorithm to generate both good lower bounds and heuristic solutions.
Abstract: We consider the problem of routing multiple commodities between various origin—destination pairs in a network, at minimum total cost. Economies of scale in arc flow costs are modeled using piecewise linear, concave total-cost functions for each arc. This model applies to a variety of medium- and long-term planning contexts including transportation planning, design of communication networks, plant location and capacity expansion planning, production planning, and water resource management. We formulate the general problem as a mixed-integer program and develop a composite algorithm to generate both good lower bounds and heuristic solutions. We also report on computational results for several randomly generated general networks (with up to 40 nodes, 359 arcs, and 60 commodities) and layered neetworks (with up to 60 nodes, 372 arcs, and 60 commodities). These tests demonstrate that even for relatively large problems, the composite algorithm is very effective in generating solutions with small gaps between the upper and lower bounds (1.7% on average for general networks, and 0.4% on average for layered networks); for 19 out of the 25 layered network problems, the method generated and verified the optimal solution.


Journal ArticleDOI
TL;DR: The design and implementation of an interactive optimization system for routing freight over a less-than-truckload motor carrier network is described, using a local improvement heuristic in such a way as to keep the “man-in-the-loop.”
Abstract: We describe the design and implementation of an interactive optimization system for routing freight over a less-than-truckload motor carrier network. We formulate a very large, mixed integer programming problem, and develop a decomposition strategy based partly on the mathematical structure of the problem as well as a range of important, real-world issues and constraints. Then we develop and implement a local improvement heuristic in such a way as to keep the “man-in-the-loop,” using the analyst to make judgments regarding certain complex constraints and tradeoffs. Important aspects of the system include a range of modeling approximations to keep the problem tractable and the way the analyst evaluates the quality of the different numbers. The package was implemented and is currently being used on an ongoing basis by a major motor carrier. An overview of the major elements of the package is given as well as a summary of important implementation issues that arose during the three year project.

Journal ArticleDOI
TL;DR: In this paper, the problem of minimizing the number of machines that the part types cross in their manufacturing process is formulated mathematically and solved by a heuristic that obtains consistently better results than an earlier popular method.
Abstract: The interconnection pattern of the processing modules of a computerized manufacturing system affects its performance. In this article, we discuss a set of requirements that the interconnection network should satisfy. Subsequently, we concentrate on a simple and popular architecture, the loop network. The problem we address is to design the layout of the system so that the number of machines that the part types cross in their manufacturing process is minimized. We formulate the problem mathematically and solve it by a heuristic that obtains consistently better results than an earlier popular method.

Journal ArticleDOI
TL;DR: This paper reviews some of the existing solution procedures, analyzes their complexity, and presents two modifications of theexisting methods to obtain near-optimal solutions for the capacitated arc routing problem.

Journal ArticleDOI
TL;DR: In this article, a two-stage branch and backtrack procedure is developed with the objective of maximizing the assigned workload with a bicriterion objective of minimizing the workload imbalance and maximizing the throughput for critical resources such as the number of tool slots on machines.
Abstract: SUMMARY The loading problem in a flexible manufacturing system (FMS) is viewed as selecting a subset of jobs from the job pool and allocating jobs among machines. A two-stage branch and backtrack procedure is developed with the objective of maximizing the assigned workload. Heuristic procedures are also developed with a bicriterion objective of minimizing the workload imbalance and maximizing the throughput for critical resources such as the number of tool slots on machines and the number of working hours in a scheduling period. The case of machine-dependent processing times is also dealt with. An illustrative numerical example accompanies each procedure.

Journal ArticleDOI
TL;DR: The multiobjective vending problem (MVP) (Keller, 1985) is a generalization of the traveling salesman problem (TSP) where it is not necessary to visit all nodes in the problem definition.

Journal ArticleDOI
TL;DR: In this article, a problem related to buffer storage allocation is formulated as a dynamic programming problem and a heuristic solution is presented, where the objective is to find optimal distribution of a total storage space among the intermediate buffers.
Abstract: One way to improve the efficiency of automatic transfer lines is to provide intermediate storage buffers. These buffers divide the transfer line into stages, each with one or more machines. The machines in a stage are completely integrated, whereas, the stages are partially decoupled. Here, we study a problem related to buffer storage allocation. The objective is to find optimal distribution of a total storage space among the intermediate buffers. This is formulated as a dynamic programming problem and a heuristic solution is presented.

Proceedings ArticleDOI
Joel L. Wolf1
01 Apr 1989
TL;DR: The FAP solution has been implemented in a PL/I program known as the Placement Optimization Program (POP), which consists of three major components — two heuristic optimization models and a queueing network model.
Abstract: In this paper we describe a practical mathematical formulation and solution of the so-called “File Assignment Problem” (FAP) for computer disks. Our FAP solution has been implemented in a PL/I program known as the Placement Optimization Program (POP). The algorithm consists of three major components — two heuristic optimization models and a queueing network model. POP has been used in validation studies to assign files to disks in two IBM MVS complexes. The resulting savings in I/O response times were 22% and 25%, respectively. Throughout the paper we shall emphasize the real-world nature of our approach to the disk FAP, which we believe sets it apart from previous attempts.

Journal ArticleDOI
TL;DR: In this article, the authors describe an automatic way of finding the least-cost method of securing a given power system by minimizing the present cost of building additional lines to make the system secure due to single contingencies.
Abstract: The authors describe an automatic way of finding the least-cost method of securing a given power system. The objective is to minimize the present cost of building additional lines to make the system secure due to single contingencies, subject to the technical constraints with and without line outages. A second approach to the problem, heuristic in nature, is also illustrated and compared to the results of the first method. All network synthesis is based on the DC power flow model. A six-bus network is used to illustrate the methods, and solutions obtained using a standard mixed-integer linear programming computer package, MIP/370, are given. >


Journal ArticleDOI
TL;DR: This paper analyzes the complete materials handling process from production at supply points to consumption at demand points and concludes that simultaneous optimization should be considered when inventory and transport strategies are developed and that the overall advantage of simultaneous optimization depends on the magnitude of the parameters.
Abstract: The need to minimize inventory, production and transport costs has long been recognized by operations researchers. Traditionally, stages in materials handling have been optimized separately. This paper analyzes the complete materials handling process from production at supply points to consumption at demand points. Reasonable assumptions are made concerning production, inventory and transport costs along with production constraints and demand requirements. A local optimum is found using a generalized reduced gradient algorithm. Initial upper and lower bounds to the solution are also derived and a heuristic is introduced which finds a solution using linear network algorithms. The reduced gradient algorithm and the heuristic are applied to a hypothetical corporate sourcing problem. The problem is a small subset of the problem of acquiring and distributing new items. Results of this analysis show that for certain cases, the value of the reduced gradient algorithm solution is very close to the value of the lo...

Journal ArticleDOI
TL;DR: In this article, the experimental design for parameter identification of a confined groundwater system is formulated as a nonlinear mixed integer programming problem, where the decision variables considered are the number and locations of the pumping and observation wells, and the pumping rates.
Abstract: The experimental design for parameter identification of a confined groundwater system is formulated as a nonlinear mixed integer programming problem The decision variables considered are the number and locations of the pumping and observation wells, and the pumping rates The constraints include the allowable drawdown, the restricted locations of pumping wells and observation wells, the permissible pumping rates, and the required information The amount of the required information is determined by the prescribed reliability of the response for the future operation of the groundwater system The Galerkin finite element-Crank Nicolson approach is used to develop the simulation models for solving the groundwater governing equation for the system responses The sensitivity coefficients are computed by the influence coefficient method The principle of superposition is used to combine the simulation models with the optimization model The characteristics of the optimization problem have been investigated and are clarified, and its difficulties are pointed out An efficient heuristic solution approach is proposed for solving this problem A test problem is constructed to demonstrate the usefulness of the proposed methodology Observations generated from the optimal design are used to identify the parameters A covariance analysis is then carried out to verify the validity of the assumptions made in the formulation of the optimization problem The results obtained indicate that the proposed methodology is feasible and can be used to solve complicated experimental design problems associated with a confined groundwater system

Journal ArticleDOI
TL;DR: Bartholdi and Platzman as discussed by the authors showed that the worst-case ratio is in fact O(1) and showed that O(lg n) upper bound is tight.

Journal ArticleDOI
TL;DR: The heuristic algorithm, which is the first phase of the branch-and-bound algorithm, has an average error of about 2%.
Abstract: In this paper, we characterize the capital budgeting problem by two objective functions. One is maximizing the present value of accepted projects and the other is minimizing their risk. As we assume that the weights assigned to these objectives are unspecified, we utilize a Discrete Efficient Frontier DEF approach to represent all the efficient combinations. We found an optimality range for each efficient combination covering the entire possible range of weights zero to one. Furthermore, we present different properties and characteristics of the DEF, and develop two algorithms for constructing the DEF. The first one is a simple heuristic and the second one is an optimal algorithm. We conducted experiments measuring the effectiveness of the heuristic algorithm and the effect of terminating the optimal algorithm before its completion. We have shown that the heuristic algorithm, which is the first phase of the branch-and-bound algorithm, has an average error of about 2%. Furthermore, we have shown that this average error can be reduced by applying only part of the optimal algorithm and terminating it before its actual completion.