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The Assembly Line Worker Assignment and Balancing Problem (ALWABP) appears in real assembly lines which we have to assign given tasks to workers where there are some task-worker incompatibilities and considering that the operation time for each task is different depending upon who executes the task. This problem is typical for Sheltered Work Centers for the Disabled and it is well known to be NP-Hard...
The well-known Vehicle Routing Problem (VRP) has been deeply studied over the last decades. Nowadays, generalizations of VRP are developed toward tactical or strategic decision levels of companies. The tactical extension plans a set of trips over a multiperiod horizon, subject to frequency constraints. The related problem is called the Periodic VRP (PVRP). On the other hand, the strategic extension...
A recent line of research concerns the integration of ant colony optimization and constraint programming. Hereby, constraint programming is used for eliminating parts of the search tree during the solution construction of ant colony optimization. In the context of a single machine scheduling problem, for example, it has been shown that the integration of constraint programming can significantly improve...
In this work we extend a VNS for the periodic vehicle routing problem with time windows (PVRPTW) to a multiple VNS (mVNS) where several VNS instances are applied cooperatively in an intertwined way. The mVNS adaptively allocates VNS instances to promising areas of the search space. Further, an intertwined collaborative cooperation with a generic ILP solver applied on a suitable set covering ILP formulation...
In this paper, we present a hybridization of an electromagnetic-like mechanism (EM) and the great deluge (GD) algorithm. This technique can be seen as a dynamic approach as an estimated quality of a new solution and a decay rate are calculated each iteration during the search process. These values are depending on a force value calculated using the EM approach. It is observed that applying these dynamic...
The development of efficient hybrid methods for solving hard optimization problems is not new in the operational research community. Some of these methods are based on the complete exploration of small neighbourhoods. In this paper, we apply iterative relaxation-based heuristics that solves a series of small sub-problems generated by exploiting information obtained from a series of relaxations to...
A Video-on-Demand system usually consists of a large number of independent video servers. In order to utilize network resources as efficiently as possible the overall network load should be balanced among the available servers. We consider a problem formulation based on an estimation of the expected number of requests per movie during the period of highest user interest. Apart from load balancing...
This paper presents the steps followed in the design of hybrid stochastic local search algorithms for biobjective permutation flow shop scheduling problems. In particular, this paper tackles the three pairwise combinations of the objectives (i) makespan, (ii) the sum of the completion times of the jobs, and (iii) the weighted total tardiness of all jobs. The proposed algorithms are combinations of...
Iterated local search is a stochastic local search (SLS) method that combines a perturbation step with an embedded local search algorithm. In this article, we propose a new way of hybridizing iterated local search. It consists in using an iterated local search as the embedded local search algorithm inside another iterated local search. This nesting of local searches and iterated local searches can...
ACO algorithms iteratively build solutions to an optimization problem. The solution construction process is guided by pheromone trails which represents a mechanism of adaptation that allows to bias the sampling of new solutions toward promising regions of the search space. Additionally, the bias of the search is influenced by problem dependent heuristic information. In this work we describe an ACO...
We present a hybrid solver (called ) that exploits the potentiality of a Constraint Programming (CP) environment (Gecode) and of a Local Search (LS) framework (EasyLocal + + ). allows to easily develop and use hybrid meta-heuristic combining CP and LS phases (in particular Large Neighborhood Search). We tested some hybrid algorithms on different instances...
We propose a multi-neighborhood local search procedure to solve a healthcare problem, known as the Patient Admission problem. We design and experiment different combinations of neighborhoods, showing that they have diverse effectiveness for different sets of weights of the cost components that constitute the objective function. We also compute some lower bounds on benchmark instances based on the...
Matheuristics are heuristic algorithms made by the interoperation of metaheuristics and mathematic programming (MP) techniques. An essential feature is the exploitation in some part of the algorithms of features derived from the mathematical model of the problems of interest, thus the definition “model-based metaheuristics” appearing in the title of some events of the conference series dedicated to...
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