The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the ...

We propose a backbone-guided tabu search (BGTS) algorithm for the Unconstrained Binary Quadratic Programming (UBQP) problem that alternates between two phases: (1) a basic tabu search procedure to optimize the objective function as far as possible; (2) a strategy using the TS notion of strongly determined variables to alternately fix and free backbone components of the solutions which are estim...

The Multiple Sequence Alignment problem is considered to be an NP-Hard problem, requiring initially a specific encoding schema and design, as for any other of its siblings, implement run the main categories heuristic. This paper intends discuss our proposed generic implementation Tabu Search algorithm, heuristic procedure by Fred Glover solve discrete combinatorial optimization problems. In thi...

We propose a tabu search meta-heuristic for the Time dependent Multi-zone Multi-trip Vehicle Routing Problem with Time Windows. Two types of neighborhoods, corresponding to two decision sets of the problem, together with a strategy controlling the selection of the neighborhood type for particular phases of the search, provide the means to set up and combine exploration and exploitation capabili...

<p style='text-indent:20px;'>We present an effective hybrid metaheuristic of integrating reinforcement learning with a tabu-search (RLTS) algorithm for solving the max–mean dispersion problem. The innovative element is to design using knowledge strategy from <inline-formula><tex-math id="M1">\begin{document}$ Q $\end{document}</tex-math></inline-formula>-learning m...

the bi-objective warehouse problem in a crisp environment is often not eective in dealing with the imprecision or vagueness in the values of the problem parameters. to deal with such situations, several researchers have proposed that the parameters be represented as fuzzy numbers. we describe a new algorithm for fuzzy bi-objective warehouse problem using a ranking function followed by an applic...

Guided Local Search originally proposed by Voudouris and Tsang [29] is a general optimisation technique suitable for a wide range of combinatorial optimisation problems. Successful applications of the technique so far include practical problems such as Frequency Allocation [29], Workforce Scheduling [28] and Vehicle Routing [2, 18] and also classic problems such as the Travelling Salesman Probl...

Constraint Programming typically uses the technique of depth-first branch and bound as the method of solving optimisation problems. Although this method can give the optimal solution, for large problems, the time needed to find the optimal can be prohibitive. This paper introduces a method for using iterative improvement techniques within a Constraint Programming framework, and applies this tec...