Search results for "ALGORITHM"
showing 10 items of 4887 documents
Fuzzy Portfolio Selection Models for Dealing with Investor’s Preferences
2017
This chapter provides an overview of the authors’ previous work about dealing with investor’s preferences in the portfolio selection problem. We propose a fuzzy model for dealing with the vagueness of investor preferences on the expected return and the assumed risk, and then we consider several modifications to include additional constraints and goals.
Impact of decision horizon on post-prognostics maintenance and missions scheduling: a railways case study
2021
International audience; In this paper, we propose a study of the decision horizon duration for rolling stock mission assignment and maintenance planning in a prognostics and health management (PHM) context. The aim is to determine the best decision horizon duration that allows the con- struction of a suitable schedule that assigns railway vehicles to missions and integrates required maintenance operations accord- ing to the current and future health of the vehicles. A genetic algorithm is used to minimize the overall cost of the joint schedule as a function of the decision horizon. The results are compared to three proposed heuristics to study the influence of the resolution method on the d…
Variable Fixing for Two-Arc Sequences in Branch-Price-and-Cut Algorithms on Path-Based Models
2020
Variable fixing by reduced costs is a popular technique for accelerating the solution process of mixed-integer linear programs. For vehicle-routing problems solved by branch-price-and-cut algorithms, it is possible to fix to zero the variables associated with all routes containing at least one arc from a subset of arcs determined according to the dual solution of a linear relaxation. This is equivalent to removing these arcs from the network used to generate the routes. In this paper, we extend this technique to routes containing sequences of two arcs. Such sequences or their arcs cannot be removed directly from the network because routes traversing only one arc of a sequence might still b…
Contributions to Branch-and-Price-and-Cut Algorithms for Routing Problems
2019
This article deals with new exact branch-and-price-and-cut algorithms for the solution of routing problems. Specialized methods for the pickup-and-delivery problem (PDP), the truck-and-trailer routing problem (TTRP), the periodic vehicle routing problem (PVRP) and a service network design and hub location problem (SNDHLP) are presented. We develop a new technique for the acceleration of bidirectional labeling algorithms by a dynamic choice of the merge point. Moreover, for variants of the PDP, the bidirectional labeling can be effectively applied for the first time. In the TTRP, we model the extension to a 2 days planning horizon and the consideration of a quantity-dependent transfer time. …
Novel Distance Estimation Methods Using 'Stochastic Learning on the Line' Strategies
2018
In this paper, we consider the problem of Distance Estimation (DE) when the inputs are the $x$ and $y$ coordinates (or equivalently, the latitudinal and longitudinal positions) of the points under consideration. The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by the latter coordinates. 1 This problem has, typically, been tackled by utilizing parametric functions called the “Distance Estimation Functions” (DEFs). The parameters are learned from the training data (i.e., the true road distances) between a subset of the points under consideration. We propose to use Learning Automata (LA)-based strategies to solve the problem. In par…
A New Branch-and-Cut Algorithm for the Generalized Directed Rural Postman Problem
2016
The generalized directed rural postman problem, also known as the close-enough arc routing problem, is an arc routing problem with some interesting real-life applications, such as routing for meter reading. In this article we introduce two new formulations for this problem as well as various families of new valid inequalities that are used to design and implement a branch-and-cut algorithm. The computational results obtained on test bed instances from the literature show that this algorithm outperforms the existing exact methods
Branch-and-Cut for the Split Delivery Vehicle Routing Problem with Time Windows
2019
The split delivery vehicle routing problem with time windows (SDVRPTW) is a notoriously hard combinatorial optimization problem. First, it is hard to find a useful compact mixed-integer programming (MIP) formulation for the SDVRPTW. Standard modeling approaches either suffer from inherent symmetries (mixed-integer programs with a vehicle index) or cannot exactly capture all aspects of feasibility. Because of the possibility to visit customers more than once, the standard mechanisms to propagate load and time along the routes fail. Second, the lack of useful formulations has rendered any direct MIP-based approach impossible. Up to now, the most effective exact algorithms for the SDVRPTW hav…
Branch-price-and-cut algorithms for the pickup and delivery problem with time windows and multiple stacks
2016
Abstract This paper proposes models and algorithms for the pickup and delivery vehicle routing problem with time windows and multiple stacks. Each stack is rear-loaded and is operated in a last-in-first-out (LIFO) fashion, meaning that when an item is picked up, it is positioned at the rear of a stack. An item can only be delivered if it is in that position. This problem arises in the transportation of heavy or dangerous material where unnecessary handling should be avoided, such as in the transportation of cars between car dealers and the transportation of livestock from farms to slaughterhouses. To solve this problem, we propose two different branch-price-and-cut algorithms. The first sol…
Applying particle swarm optimization to the motion-cueing-algorithm tuning problem
2017
The MCA tuning problem consists in finding the best values for the parameters/coefficients of Motion Cueing Algorithms (MCA). MCA are used to control the movements of robotic motion platforms employed to generate inertial cues in vehicle simulators. This problem is traditionally approached with a manual pilot-in-the-loop subjective tuning, based on the opinion of several pilots/drivers. Instead, this paper proposes applying Particle Swarm Optimization (PSO) to solve this problem, using simulated motion platforms and objective indicators rather than subjective opinions. Results show that PSO-based tuning can provide a suitable solution for this complex optimization problem.
Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design.
2016
Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial accelera…