Constructive Heuristic Algorithm Research Articles

Constructive heuristic algorithm for the DC model in network transmission expansion planning

A novel constructive heuristic algorithm to the network expansion planning problem is presented. The basic idea comes from Garver's work applied to the transportation model, nevertheless the proposed algorithm is for the DC model. Tests results with most known systems in the literature are carried out to show the efficiency of the method.

Two‐machine open shop scheduling with secondary criteria

This paper considers two‐machine open shop problems with secondary criteria where the primary criterion is the minimization of makespan and the secondary criterion is the minimization of the total flow time, total weighted flow time, or total weighted tardiness time. In view of the strongly NP‐hard nature of these problems, two polynomially solvable special cases are given and constructive heuristic algorithms based on insertion techniques are developed. A strongly connected neighborhood structure is derived and used to develop effective iterative heuristic algorithms by incorporating iterative improvement, simulated annealing and multi‐start procedures. The proposed insertion and iterative heuristic algorithms are empirically evaluated by solving problem instances with up to 80 jobs.

Analysis of heuristic algorithms for the transportation model in static and multistage planning in network expansion systems

The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.

Constructive and improvement flow shop scheduling heuristics: An extensive evaluation

A number of optimization techniques are available to solve the scheduling problems. Most of the scheduling problems are combinatorial optimization problems which are too difficult to be solved optimally, and hence heuristics are used to obtain 'good' solutions in reasonable time. Scheduling deals with the allocation of resources. Scheduling is a decision-making process that has, as a goal, the optimization of two or more objectives. The specific goal of this paper is to perform a comparative evaluation of the exisiting constructive heuristic algorithms and to propose an improvement heuristic algorithm. The improvement heuristic algorithm proposed is a genetic algorithm. The benchmark problems are used to evaluate these algorithms. The genetic algorithm (GA) is a potentially powerful tool for solving complex optimization problems. In this paper, the heuristic procedures considered for evaluation are Palmer's algorithm, Gupta's algorithm, C D S algorithm, Dannenbring's R A algorithm, N E H algorithm and the proposed genetic algorithm. The algorithms are coded in G language. The performance measure considered for evaluation is the makespan.

A new matrix bandwidth reduction algorithm

The problem that we address is, given a matrix, permute rows and columns so that the bandwidth is minimized. Several constructive heuristic algorithms have been proposed in the literature to reduce the bandwidth of symmetrically structured matrices. However, these methods are often ineffective when applied to some pathological cases. In the present paper we propose a new heuristic obtained as an improvement of the classical Cuthill McKee algorithm. From the computational results it appears that the new algorithm overcomes the pathological cases where the literature algorithm get stuck. The algorithm is applied to data from real applications. A comparison on real cases is also made with previous constructive approaches demonstrating the superior performance of the here proposed method.

Constructive heuristic algorithms for the open shop problem

In this paper we consider constructive heuristic algorithms for the open shop problem with minimization of the schedule length. By means of investigations of the structure of a feasible solution two types of heuristic algorithms are developed: construction of a rank-minimal schedule by solving successively weighted maximum cardinality matching problems and construction of an approximate schedule by applying insertion techniques combined with beam search. All presented algorithms are tested on benchmark problems from the literature. Our computational results demonstrate the excellent solution quality of our insertion algorithm, especially for greater job and machine numbers. For 29 of 30 benchmark problems with at least 10 jobs and 10 machines we improve the best known values obtained by tabu search.

A constructive heuristic algorithm for concurrently selecting and sequencing jobs in an FMS environment

This paper deals with the concurrent solution of the loading and scheduling problems in a flexible manufacturing system ( FMS) environment. It is assumed that the FMS environment has production planned periodically and each job in the system has a number of operations to be processed on flexible machines. A heuristic approach using a constructive scheduling method is developed to solve the FMS loading and scheduling problems concurrently. The computational results are compared to an existing procedure that considers a hierarchical approach with a similar problem environment. The comparison study shows a significant improvement over the existing hierarchical procedure. This experiment indicates that a concurrent solution approach can solve the FMS loading and scheduling problems very effectively.

A construction algorithm for the selection and assignment of materials handling equipment

A model for selecting materials handling equipment and assigning it to departmental moves is presented. The problem is formulated as an integer program with the objective of minimizing the total operating and investment costs of the selected equipment. The constraints specify that each move is restricted to only one equipment type and the available operating time of each equipment type cannot be exceeded. The problem is solved using a construction heuristic algorithm that exploits, conceptually, some similarities to both the knapsack and the loading problems. The algorithm is computationally attractive and lends to achieve other goals, such as maximizing equipment utilization and minimizing the variations in equipment types, as well as the primary goal of cost minimization.

An Efficient Equipment-Layout Algorithm

This paper treats the problem of locating a given number of interrelated physical facilities in a single- or multi-story building as an optimization model such that the weighted sum of the distances along orthogonal directions is minimized, and describes a constructive heuristic algorithm for the one-dimensional model. This linear placement algorithm is then extended to higher dimensions for placing uniform-size equipment modules at homogeneous fixed locations. The algorithm accommodates lower-bound constraints for the linear case efficiently and produces near-optimal solutions. Its significance, as demonstrated by comparison with some existing heuristic procedures, is that it has the capability of handling efficiently problems with large numbers of equal-size facilities whose solutions are computationally intractable using the present optimum-producing methods.