Results 1 - 10
of
16
Cluster analysis and mathematical programming
- MATHEMATICAL PROGRAMMING
, 1997
"... ..."
(Show Context)
An Integer Linear Programming Approach and a Hybrid Variable Neighborhood Search for the Car Sequencing Problem
, 2005
"... In this paper we present two major approaches to solve the car sequencing problem, in which the goal is to find an optimal arrangement of commissioned vehicles along a production line with respect to constraints of the form “no more than lc cars are allowed to require a component c in any subsequenc ..."
Abstract
-
Cited by 11 (0 self)
- Add to MetaCart
In this paper we present two major approaches to solve the car sequencing problem, in which the goal is to find an optimal arrangement of commissioned vehicles along a production line with respect to constraints of the form “no more than lc cars are allowed to require a component c in any subsequence of mc consecutive cars”. The first method is an exact one based on integer linear programming (ILP). The second approach is hybrid: it uses ILP techniques within a general variable neighborhood search (VNS) framework for examining large neighborhoods. We tested the two methods on benchmark instances provided by CSPlib and the automobile manufacturer RENAULT for the ROADEF Challenge 2005. These tests reveal that our approaches are competitive to previous reported algorithms. For the CSPlib instances we were able to shorten the required computation time for reaching and proving optimality. Furthermore, we were able to obtain tight bounds on some of the ROADEF instances. For two of these instances the proposed ILP-method could provide new optimality proofs for already known solutions. For the VNS, the individual
Combining Variable Neighborhood Search with Integer Linear Programming for the Generalized Minimum Spanning Tree Problem
, 2006
"... We consider the generalized version of the classical Minimum Spanning Tree problem where the nodes of a graph are partitioned into clusters and exactly one node from each cluster must be connected. We present a Variable Neighborhood Search (VNS) approach which uses three different neighborhood types ..."
Abstract
-
Cited by 9 (5 self)
- Add to MetaCart
We consider the generalized version of the classical Minimum Spanning Tree problem where the nodes of a graph are partitioned into clusters and exactly one node from each cluster must be connected. We present a Variable Neighborhood Search (VNS) approach which uses three different neighborhood types. Two of them work in complementary ways in order to maximize search effectivity. Both are large in the sense that they contain exponentially many candidate solutions, but efficient polynomial-time algorithms are used to identify best neighbors. For the third neighborhood type we apply Mixed Integer Programming to optimize local parts within candidate solution trees. Tests on Euclidean and random instances with up to 1280 nodes indicate especially on instances with many nodes per cluster significant advantages over previously published metaheuristic approaches.
Bringing order into the neighborhoods: relaxation guided variable neighborhood search
- J. of Heuristics
"... ..."
Scheduling workover rigs for onshore oil production
- Discrete Applied Mathematics
, 2006
"... Many oil wells in Brazilian onshore fields rely on artificial lift methods. Mainte-nance services such as cleaning, reinstatement, stimulation and others are essential to these wells. These services are performed by workover rigs, which are available on a limited number with respect to the number of ..."
Abstract
-
Cited by 6 (1 self)
- Add to MetaCart
(Show Context)
Many oil wells in Brazilian onshore fields rely on artificial lift methods. Mainte-nance services such as cleaning, reinstatement, stimulation and others are essential to these wells. These services are performed by workover rigs, which are available on a limited number with respect to the number of wells demanding service. The decision of which workover rig should be sent to perform some maintenance service is based on factors such as the well production, the current location of the workover rig in relation to the demanding well, and the type of service to be performed. The problem of scheduling workover rigs consists in finding the best schedule for the available workover rigs, so as to minimize the production loss associated with the wells awaiting for service. We propose a VNS heuristic for this problem. Compu-tational results on real-life problems are reported and their economic impacts are evaluated.
Disco-novo-gogo: Integrating local search and complete saerch with restarts
- In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI06
, 2006
"... Abstract A hybrid algorithm is devised to boost the performance of complete search on under-constrained problems. We suggest to use random variable selection in combination with restarts, augmented by a coarse-grained local search algorithm that learns favorable value heuristics over the course of ..."
Abstract
-
Cited by 5 (0 self)
- Add to MetaCart
(Show Context)
Abstract A hybrid algorithm is devised to boost the performance of complete search on under-constrained problems. We suggest to use random variable selection in combination with restarts, augmented by a coarse-grained local search algorithm that learns favorable value heuristics over the course of several restarts. Numerical results show that this method can speedup complete search by orders of magnitude.
Relaxation Guided Variable Neighborhood Search
- Proceedings of the 18th Mini Euro Conference on Variable Neighborhood Search
, 2005
"... In this article we investigate a new variant of Variable Neighborhood Search (VNS): Relaxation Guided Variable Neighborhood Search. It is based on the general VNS scheme and a new Variable Neighborhood Descent (VND) algorithm. The ordering of the neighborhood structures in this VND is determined ..."
Abstract
-
Cited by 5 (2 self)
- Add to MetaCart
In this article we investigate a new variant of Variable Neighborhood Search (VNS): Relaxation Guided Variable Neighborhood Search. It is based on the general VNS scheme and a new Variable Neighborhood Descent (VND) algorithm. The ordering of the neighborhood structures in this VND is determined by solving relaxations of them. The objective values of these relaxations are used as indicators for the potential gains of searching the corresponding neighborhoods. We tested this new approach on the well-studied multidimensional knapsack problem. Computational experiments show that our approach is beneficial to the search, improving the obtained results.
Computing Generalized Minimum Spanning Trees with Variable Neighborhood Search
- In Proceedings of the 18th Mini-Euro Conference on Variable Neighborhood Search
, 2005
"... In the generalized version of the classical Minimum Spanning Tree problem, the nodes of a graph are partitioned into clusters and exactly one node from each cluster must be connected. This problem plays, for example, a role in the design of backbones in larger communication networks. We present a Va ..."
Abstract
-
Cited by 4 (2 self)
- Add to MetaCart
(Show Context)
In the generalized version of the classical Minimum Spanning Tree problem, the nodes of a graph are partitioned into clusters and exactly one node from each cluster must be connected. This problem plays, for example, a role in the design of backbones in larger communication networks. We present a Variable Neighborhood Search (VNS) approach for this problem which is based on two different neighborhood types working in complementary ways to maximize the efficiency gained from the VNS concept. Both types of neighborhoods are large in the sense that they contain exponentially many candidate solutions, but efficient polynomial-time algorithms are used to identify best neighbors. Tests on Euclidean and random instances indicate in particular on instances with many nodes per cluster significant advantages of our VNS over previously published metaheuristic approaches.
Large Neighborhood Search for rich VRP with multiple pickup and delivery locations
- in Proceedings of the 18th Mini EURO Conference on VNS (MEC-VNS
, 2005
"... In this paper we consider a rich vehicle routing problem where transportation requests are characterised by multiple pickup and delivery locations. The problem is a combined load acceptance and generalised vehicle routing problem incorporating a diversity of practical complexities. Among those are t ..."
Abstract
-
Cited by 3 (2 self)
- Add to MetaCart
(Show Context)
In this paper we consider a rich vehicle routing problem where transportation requests are characterised by multiple pickup and delivery locations. The problem is a combined load acceptance and generalised vehicle routing problem incorporating a diversity of practical complexities. Among those are time window restrictions, a heterogeneous vehicle fleet with different travel times, travel costs and capacity, multi-dimensional capacity constraints, order/vehicle compatibility constraints, and different start and end locations for vehicles. We propose iterative improvement approaches based on Large Neighborhood Search and a relatedness measure for transportation requests with multiple pickup and delivery locations. Our algorithms are characterised by very fast response times and thus, can be used within dynamic routing systems where input data can change at any time.
