tabu search algorithm

Today, the uncertainty in the estimated time and cost of industrial projects is considered as an important challenge in the science of project management. If risk management is done regularly to identify potential problems and find their solution, it will easily complement other processes such as organizing, planning, budgeting, and cost control. In this regard, one of the most important and effective solutions to this problem is risk analysis (primary, secondary, and residual). In this research, an optimization model has been proposed to select actions to respond to risk for all three primary, secondary and residual risks. This research is quantitative. In building the model, the objective function is to minimize the total risk costs and the costs of reducing the time constraints applied to the relationship between two activities. Then, by determining a suitable reasonable time for the whole project and solving the model, an optimal set of actions to respond to the risks is determined. The basic innovation of this research, which does not cause the selection of a predetermined strategy, is the two limitations that examine the two dimensions of time and cost in response to primary and secondary risk. The results indicate that the initial risk costs have decreased. Also, by responding to the primary risk, secondary risks were created, which imposed a cost on the system, but this cost was reduced by assigning secondary strategies, as well as the optimal cost of activity failure with the sensitivity analysis that was done, the maximum amount of time that the project can end It was equal to 78 days and more than that makes the cost of failure of activities to be zero. Also, in this research, the genetic meta-heuristic algorithm and the Particle swarm algorithm were used to solve the problem in high dimensions, and the results showed that there is no difference in the results of these two algorithms.

Job shop scheduling problem (JSP) is an attractive field for researchers and production managers since it is a famous problem in many industries and a complex problem for researchers. Due to NP-hardness property of this problem, many meta-heuristics are developed to solve it. Solution representation (solution seed) is an important element for any meta-heuristic algorithm. Therefore, many researchers try to present different encodings to solve this problem. Fattahi et al., and Gen & Cheng suggested two solutions for this problem that both have advantages and weaknesses in searching solution space to reach an acceptable solution. In the current paper, a cyclic algorithm based on tabu search algorithm was proposed to improve the exploration and exploitation powers of these encodings. Also, several problems of different sizes are solved by it and the obtained results were compared. Results showed the applicability and effectiveness of the proposed solution representation in comparison with the existing ones

In this paper, a leader–follower competitive facility location problem considering the reactions of the competitors is studied. A model for locating new facilities and determining levels of quality for the facilities of the leader firm is proposed. Moreover, changes in the location and quality of existing facilities in a competitive market where a competitor offers the same goods or services are taken into account. The competitor could react by opening new facilities, closing existing ones, and adjusting the quality levels of its existing facilities. The market share, captured by each facility, depends on its distance to customer and its quality that is calculated based on the probabilistic Huff’s model. Each firm aims to maximize its profit subject to constraints on quality levels and budget of setting up new facilities. This problem is formulated as a bi-level mixed integer non-linear model. The model is solved using a combination of Tabu Search with an exact method. The performance of the proposed algorithm is compared with an upper bound that is achieved by applying Karush–Kuhn–Tucker conditions. Computational results show that our algorithm finds near the upper bound solutions in a reasonable time.

The recent years have witnessed an increasing attention to the methods of multiple attribute decision making in solving the problems of the real world due to their shorter time of calculation and easy application. One of these methods is the ‘permutation method’ which has a strong logic in connection with ranking issues, but when the number of alternatives increases, solving problems through this method becomes NP-hard. So, meta-heuristic algorithm based on Tabu search is used to find optimum or near optimum solutions at a reasonable computational time for large size problems. This research is an attempt to apply the ‘permutation method’ to rank some countries of the West Asia and the North Africa based on the development criteria. Knowing the situation of each country as compared with other countries, particularly the respective neighbouring countries, is one of the most important standards for the assessment of performance and planning for the future activities.