Problems in operations research are often NP complete and optimal solution for larger problems cannot be obtained, therefore heuristic methods have to be used. The boundary between the size of the problem that can be solved optimally and those where heuristic methods should be used is not always clear. To solve this problem we propose a method based on decision trees. The method can be also use...

The main challenge of automated theorem proving is to find a way to shorten the search process. Therefore using a good heuristic method is essential. Instead of constructing a heuristic from scratch, we propose to use the mixture of experts learning to combine the existing heuristics to construct a heuristic from similar problems. The results show that the combined heuristic is better than each...

A heuristic method for solving large-scale multi–facility location problems is presented. The method is analogous to Cooper’s method [3], using the authors’ single facility location method [20] as a parallel subroutine, and reassigning customers to facilities using the heuristic of Nearest Center Reclassification. Numerical results are reported.

This paper presents three heuristic functions that aim to reduce the search cost for the knight tour problem. The first heuristic, h1a, is an interesting case of study that illustrates heuristic analysis, although it fails to obtain solutions. Heuristic h2 is an enhancement of the Warnsdorff method, discussed as heuristic h1b. All heuristics are used in conjunction with a greedy algorithm to de...

We propose a structure-exploiting heuristic for the justification-based stochastic local search (SLS) method CRSat for Boolean circuit satisfiability. Experimental evaluation shows that the proposed depth-based heuristic significantly improved the performance of CRSat on structural instances arising from industrial applications. A proof of probabilistically approximate completeness (PAC) of CRS...

In method-based software development, software engineers create artifacts based on the heuristic rules of the adopted method. Most CASE tools, however, do not actively assist software engineers in applying the heuristic rules. To provide an active support, the rules must be formalized, implemented and integrated within the framework of current CASE tools. In this paper we describe an approach f...

assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. in this study, we solve quadratic assignment problem (qap), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. it should be noted that any facility must be assign to only one location. in this paper, first o...

The solutions used to solve bi-level congestion pricing problems are usually based on heuristic network optimization methods which may not be able to find the best solution for these type of problems. The application of meta-heuristic methods can be seen as viable alternative solutions but so far, it has not received enough attention by researchers in this field. Therefore, the objective of thi...

This article addresses a multi-stage flowshop scheduling problem with equal number of unrelated parallel machines. The objective is to minimize the makespan for a given set of jobs in the system. This problem class is NP-hard in the strong sense, so a hybrid heuristic method for sequencing and then allocating operations of jobs to machines is developed. A number of test problems are randomly ge...

fuzzy cognitive maps (fcms) have successfully been applied in numerous domains to show the relations between essential components in complex systems. in this paper, a novel learning method is proposed to construct fcms based on historical data and by using meta-heuristic: genetic algorithm (ga), simulated annealing (sa), and tabu search (ts). implementation of the proposed method has demonstrat...