A Modified Staged Continuous Tabu Search Algorithm

Abstract

-Based on the staged continuous tabu search (SCTS) algorithm, a modified staged continuous tabu search (MSCTS) algorithm is proposed in this paper to improve the convergence, speed and robustness of tabu search (TS) algorithm. The improvements focus on the selection method of the neighborhoods in MSCTS algorithm. The generation of neighborhoods is guided by the multidimensional normal distribution function. In multidimensional normal distribution function, the mean value is the current optimal solution and the standard deviation is produced by the difference vector of the objective function at the current optimal solution. The range setting of neighborhood is different at different stage. 9 typical functions are used to test the performance of MSCTS and SCTS algorithm respectively. There are 5 indexes to evaluate the performance of both algorithms. The tests results show that MSCTS algorithm is good at dealing with the multivariate optimization problems. The calculated optimum solution for multi-variable function by MSCTS algorithm is about 5 to 17 times as near to the theoretical optimum solution as that of SCTS algorithm. As to the same test function, the calculation speed of MSCTS algorithm is about 3 to 17 times as many as that of SCTS algorithm. At the same time, the application of MSCTS algorithm is more extensive.Index Terms -Global optimization, Tabu search algorithm, Neighborhoods structure, Selection range I . IntroductionOptimization technology is widely applied in a variety of fields, such as engineering design, science analysis and financial data treatment. With computer technology getting increasingly powerful, optimization technology attracts more and more researchers' interests.Tabu search (TS) algorithm is one of crucial global optimization techniques. TS algorithm was first proposed by Professor Glover in 1986, from University of Colorado [1-2], for solving combinatorial optimization problems. The essential characteristic of TS algorithm is that several optimal solutions found temporarily, called taboo objects, are recorded by tabu list, which prevents these taboo objects can be found again in next several iterations. The existence of tabu list persecutes computer to turn to another direction to find better solutions, so as to jump out of local optimal effectively.Like other global optimization techniques, TS algorithm is applied in a variety of fields, too. In chemical engineering, TS algorithm was used to find good model parameters for metabolic flux analysis (MFA) problems [3]. This method was also reported to be used in facility layout to improve the efficiency of material handing within a manufacturing system [4]. In addition, TS algorithm was reported to be used for structural software testing [5].Although TS algorithm can get global optimum by tabu list, the probability of being trapped in a local optimum still exists. Many method were proposed to solve this kind shortage, such as using a specific neighborhood definition which employs a block of jobs notion [6], employing a flex...

Intelligent optimal control for the crawler vehicle with semi-active suspension using modified staged continuous tabu search algorithm

“…Actually, MSCTS can narrow down to the true global optimum by shrinking searching boundary and searching step from stage to stage, which also helps to reduce computation complexity and improve searching accuracy. Figure 4 shows the flow chart of one stage searching process in MSCTS (Wang et al, 2013). After neighbors generated around current optimum in every iteration, the repeated new possible optimum will be recorded in tabu list, because the repeated one might be the local optimum.…”

“…Inspired by the semi-active suspension technology and the comprehensive control method, this paper proposes a novel control strategy to solve contradictory requirements of crawler vehicles for different performances. Based on crawler vehicle semi-active suspension system dynamic model, the proposed method also employs modified staged continuous tabu search (MSCTS) algorithm, which is a kind of intelligent optimal algorithm (Wang et al, 2013) for searching global optimum rapidly. In detail, MSCTS strives to search optimal solutions of penalty function as the controllable damping ratio for semi-active suspension without requiring training data support.…”