Improving dense packings of equal disks in a square.
Integer programming approaches for minimum stabbing problems
The problem of finding structures with minimum stabbing number has received considerable attention from researchers. Particularly, [10] study the minimum stabbing number of perfect matchings (mspm), spanning trees (msst) and triangulations (mstr) associated to set of points in the plane. The complexity of the mstr remains open whilst the other two are known to be 𝓝𝓟-hard. This paper presents integer programming (ip) formulations for these three problems, that allowed us to...
Large Neighborhood Local Search for the P-Median Problem
Learnheuristics: hybridizing metaheuristics with machine learning for optimization with dynamic inputs
This paper reviews the existing literature on the combination of metaheuristics with machine learning methods and then introduces the concept of learnheuristics, a novel type of hybrid algorithms. Learnheuristics can be used to solve combinatorial optimization problems with dynamic inputs (COPDIs). In these COPDIs, the problem inputs (elements either located in the objective function or in the constraints set) are not fixed in advance as usual. On the contrary, they might vary in a predictable (non-random)...
Limit cycle prediction based on evolutionary multiobjective formulation.
Mathematical solutions for solving periodic railway transportation.
MEMOTS: a memetic algorithm integrating tabu search for combinatorial multiobjective optimization
We present in this paper a new multiobjective memetic algorithm scheme called MEMOX. In current multiobjective memetic algorithms, the parents used for recombination are randomly selected. We improve this approach by using a dynamic hypergrid which allows to select a parent located in a region of minimal density. The second parent selected is a solution close, in the objective space, to the first parent. A local search is then applied to the offspring. We experiment this scheme with a new multiobjective...
Metaheuristics based on Bin Packing for the line balancing problem
The line balancing problem consits in assigning tasks to stations in order to respect precedence constraints and cycle time constraints. In this paper, the cycle time is fixed and the objective is to minimize the number of stations. We propose to use metaheuristics based on simulated annealing by exploiting the link between the line balancing problem and the bin packing problem. The principle of the method lies in the combination between a metaheuristic and a bin packing heuristic. Two representations of...
MIP-based heuristics for multi-item capacitated lot-sizing problem with setup times and shortage costs
We address a multi-item capacitated lot-sizing problem with setup times that arises in real-world production planning contexts. Demand cannot be backlogged, but can be totally or partially lost. Safety stock is an objective to reach rather than an industrial constraint to respect. The problem is NP-hard. We propose mixed integer programming heuristics based on a planning horizon decomposition strategy to find a feasible solution. The planning horizon is partitioned into several sub-horizons over...
Modelling of the automatic depth control electrohydraulic system using RBF neural network and genetic algorithm.
Modified PSO method for robust control of 3RPS parallel manipulators.
Modified T-F function method for finding global minimizer on unconstrained optimization.
Multidimensional assignment: applications and some thoughts.
Multiobjective output feedback control of a class of stochastic hybrid systems with state-dependent noise.
Multi-swarm that learns
Multi-working modes product-color planning based on evolutionary algorithms and swarm intelligence.
New algorithms for coupled tasks scheduling – a survey
The coupled tasks scheduling problem is a class of scheduling problems introduced for beam steering software of sophisticated radar devices, called phased arrays. Due to increasing popularity of such radars, the importance of coupled tasks scheduling is constantly growing. Unfortunately, most of the coupled tasks problems are NP-hard, and only a few practically usable algorithms for such problems were found. This paper provides a survey of already known complexity results of various variants of...
Niching mechanisms in evolutionary computations
Different types of niching can be used in genetic algorithms (GAs) or evolutionary computations (ECs) to sustain the diversity of the sought optimal solutions and to increase the effectiveness of evolutionary multi-objective optimization solvers. In this paper four schemes of niching are proposed, which are also considered in two versions with respect to the method of invoking: a continuous realization and a periodic one. The characteristics of these mechanisms are discussed, while as their performance...
Non orthogonal cutting problem the case of trapezoidal pieces.
Nonlinear nonconvex optimization by evolutionary algorithms applied to robust control.