in this paper, a robust model presented is developed for hub covering flow problem in which hubs have capacity. this problem has two objective functions converting to a single-objective problem by using weighting method. firstly, the problem will be formulated in a certain case. then, by considering the demand as a non-random variable, it will be modeled by robust optimization. finally, by usin...

the capacitated vehicle routing problem (cvrp) is a well-known combinatorial optimization problem that holds a central place in logistics management. the vehicle routing is an applied task in the industrial transportation for which an optimal solution will lead us to better services, save more time and ultimately increase in customer satisfaction. this problem is classified into np-hard problem...

The NP-hard capacitated clustering problem (CCP) is a general model with a number of relevant applications. This paper proposes a highly effective iterated variable neighborhood search (IVNS) algorithm for solving the problem. IVNS combines an extended variable neighborhood descent method and a randomized shake procedure to explore effectively the search space. The computational results obtaine...

In the Categorical Clustering problem, we are given a set of vectors (matrix) A={a1,…,an} over Σm, where Σ is finite alphabet, and integers k B. The task to partition A into clusters such that median objective clustering in Hamming norm at most Fomin, Golovach, Panolan [ICALP 2018] proved problem fixed-parameter tractable for binary case Σ={0,1}. We extend this algorithmic result popular capaci...

In this paper we present a hybrid heuristic for the capacitated pmedian problem (CPMP). This problem considers a set of n points, each of them with a known demand, the objective consists of finding p medians and assign each point to exactly one median such that the total distance of assigned points to their corresponding medians is minimized, and the a capacity limit on the medians may not be e...

This paper presents two multilevel refinement algorithms for the capacitated clustering problem. Multilevel refinement is a collaborative technique capable of significantly aiding the solution process for optimisation problems. The central methodologies of the technique are filtering solutions from the search space and reducing the level of problem detail to be considered at each level of the s...

In this work, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between randomization and greediness on the performance of these multi-start heuristic search methods when solving this NP-hard problem. The former is a memory-le...