References of "Crama, Yves"
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See detailEditorial: Sweet sixteen
Crama, Yves ULiege; Grabisch, Michel; Martello, Silvano

in 4OR (2018)

This is the traditional triennial note used by the editors to give the readers of 4OR information on the state of the journal and its future. In the 3years that have passed since the last editorial note ... [more ▼]

This is the traditional triennial note used by the editors to give the readers of 4OR information on the state of the journal and its future. In the 3years that have passed since the last editorial note (Liberti et al. in Q J Oper 13:1–13, 2015), three volumes (each containing four issues) of the journal have been published: vol. 13 (2015), vol. 14 (2016), and vol. 15 (2017). [less ▲]

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See detailReformulations of nonlinear binary optimization problems
Crama, Yves ULiege

Scientific conference (2018, March)

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See detailStochastic Inventory Routing for Perishable Products
Crama, Yves ULiege; Rezaei Sadrabadi, Mahmood ULiege; Savelsbergh, Martin et al

in Transportation Science (2018)

Different solution methods are developed to solve an inventory routing problem for a perishable product with stochastic demands. The solution methods are compared empirically in terms of average profit ... [more ▼]

Different solution methods are developed to solve an inventory routing problem for a perishable product with stochastic demands. The solution methods are compared empirically in terms of average profit, service level, and actual freshness. The benefits of explicitly considering demand uncertainty are quantified. The computational study highlights that in certain situations a simple ordering policy can already reach a very good performance, but that statistically and economically significant improvements are achieved when using more advanced solution methods. Managerial insights concerning the impact of shelf life and store capacity on profit are also obtained. [less ▲]

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See detailSpecial issue: Twelfth Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015)
Crama, Yves ULiege; Goossens, Dries; Leus, Roel et al

in Journal of Scheduling (2017), 20(6), 543-711

This special issue of the Journal of Scheduling contains ten papers presented at the Twelfth Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015), held from June 8 to June ... [more ▼]

This special issue of the Journal of Scheduling contains ten papers presented at the Twelfth Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015), held from June 8 to June 12, 2015, in La Roche-en-Ardenne, Belgium. [less ▲]

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See detailTesting revealed preference: An algorithmic outlook
Smeulders, Bart ULiege; Crama, Yves ULiege; Spieksma, Frits C.R.

E-print/Working paper (2017)

Revealed preference theory is a domain within economics that studies rationalizability of behavior by (certain types of) utility functions. Given observed behavior in the form of choice data, testing ... [more ▼]

Revealed preference theory is a domain within economics that studies rationalizability of behavior by (certain types of) utility functions. Given observed behavior in the form of choice data, testing whether certain conditions are satisfied gives rise to a variety of computational problems that can be analyzed using operations research techniques. In this survey, we provide an overview of these problems, their theoretical complexity, and available algorithms for tackling them. We focus on consumer choice settings, in particular individual choice, collective choice and stochastic choice settings. [less ▲]

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See detailNeighborhood search approaches for a multi-trip vehicle routing problem with time windows
François, Véronique ULiege; Arda, Yasemin ULiege; Crama, Yves ULiege

Conference (2017, July 10)

We consider a multi-trip vehicle routing problem with time windows where each vehicle can perform several routes to serve the customers. Besides imposing a time window at the depot, we also assume that ... [more ▼]

We consider a multi-trip vehicle routing problem with time windows where each vehicle can perform several routes to serve the customers. Besides imposing a time window at the depot, we also assume that the working time of each vehicle may not exceed a maximum duration. The pursued objective is the minimization of the total working time. In this context, starting early to ensure the satisfaction of time window constraints has a negative impact on the objective function and on the maximum allowed working time constraint. Thus, vehicle start times are explicit decision variables. We compare two large neighborhood search approaches. The first one combines vehicle routing heuristics with bin packing techniques aimed at assigning routes to vehicles. The second one makes use of specific multi-trip operators designed to tackle simultaneously the routing and the assignment aspects of the problem. We show that the proposed multi-trip operators are more suitable for constrained instances with tight time windows. An automatic configuration tool is used to find high quality results. Moreover, it allows us to gain knowledge about the behavior of algorithmic components. We also question the impact of commonly employed heuristic components. [less ▲]

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See detailA class of valid inequalities for multilinear 0-1 optimization problems
Rodriguez Heck, Elisabeth ULiege; Crama, Yves ULiege

Conference (2017, March 13)

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See detailMulti-period vehicle allocation with uncertain transportation requests
Crama, Yves ULiege; Pironet, Thierry ULiege

E-print/Working paper (2017)

This work investigates optimization techniques for a multi-period vehicle allocation problem with uncertain requests. A company owning a limited fleet of trucks attempts to maximize its operational profit ... [more ▼]

This work investigates optimization techniques for a multi-period vehicle allocation problem with uncertain requests. A company owning a limited fleet of trucks attempts to maximize its operational profit over an infinite horizon by optimally assigning transportation orders to the vehicles. Its profit stems from profits collected when transporting full truckloads, minus costs incurred when waiting or when moving unladen. The stochastic component of the problem arises from the uncertainty on the realization of each transportation order. The methodology is based on optimizing decisions for deterministic scenarios. Several policies are generated in this way, either by simple heuristics, or by more complex approaches, such as consensus and restricted expectation algorithms, or from network flow formulations over subtrees of scenarios. Myopic and a-posteriori deterministic optimization models are used to compute bounds allowing for performance evaluation. Numerical experiments are performed on various instances featuring different numbers of orders, graph sizes, sparsity, and probability distributions, and the performance of the algorithms is assessed by statistical tests. The robustness of various policies with respect to erroneous evaluations of the probability distributions is also analyzed. [less ▲]

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See detailAdaptive large neighborhood search for multi-trip vehicle routing with time windows
François, Véronique ULiege; Arda, Yasemin ULiege; Crama, Yves ULiege

E-print/Working paper (2017)

We consider a multi-trip vehicle routing problem with time windows (MTVRPTW), in which each vehicle can perform several trips during its working shift. This problem is especially relevant in the context ... [more ▼]

We consider a multi-trip vehicle routing problem with time windows (MTVRPTW), in which each vehicle can perform several trips during its working shift. This problem is especially relevant in the context of city logistics. Heuristic solution methods for multi-trip vehicle routing problems often separate routing and assignment phases in order to create trips and then assign them to the available vehicles. We show that this approach is outperformed by an integrated solution method in the presence of time windows. We use an automatic configuration tool to obtain efficient and contextualized implementations of our solution methods. We provide suitable instances for the MTVRPTW as well as an instance generator. Also, we discuss the relevance of two objective functions: the total duration and the total travel time. When minimizing the travel time, large increases of waiting time are incurred, which is not realistic in practice. [less ▲]

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See detailA class of valid inequalities for multilinear 0-1 optimization problems
Crama, Yves ULiege; Rodriguez Heck, Elisabeth ULiege

in Discrete Optimization (2017), 25

This paper investigates the polytope associated with the classical standard linearization technique for the unconstrained optimization of multilinear polynomials in 0-1 variables. A new class of valid ... [more ▼]

This paper investigates the polytope associated with the classical standard linearization technique for the unconstrained optimization of multilinear polynomials in 0-1 variables. A new class of valid inequalities, called 2-links, is introduced to strengthen the LP relaxation of the standard linearization. The addition of the 2-links to the standard linearization inequalities provides a complete description of the convex hull of integer solutions for the case of functions consisting of at most two nonlinear monomials. For the general case, various computational experiments show that the 2- links improve both the standard linearization bound and the computational performance of exact branch & cut methods. The improvements are especially significant for a class of instances inspired from the image restoration problem in computer vision. The magnitude of this effect is rather surprising in that the 2-links are in relatively small number (quadratic in the number of terms of the objective function). [less ▲]

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See detailQuadratic reformulations of nonlinear binary optimization problems
Anthony, Martin; Boros, Endre; Crama, Yves ULiege et al

in Mathematical Programming (2017), 162

Very large nonlinear unconstrained binary optimization problems arise in a broad array of applications. Several exact or heuristic techniques have proved quite successful for solving many of these ... [more ▼]

Very large nonlinear unconstrained binary optimization problems arise in a broad array of applications. Several exact or heuristic techniques have proved quite successful for solving many of these problems when the objective function is a quadratic polynomial. However, no similarly efficient methods are available for the higher degree case. Since high degree objectives are becoming increasingly important in certain application areas, such as computer vision, various techniques have been recently developed to reduce the general case to the quadratic one, at the cost of increasing the number of variables. In this paper we initiate a systematic study of these quadratization approaches. We provide tight lower and upper bounds on the number of auxiliary variables needed in the worst-case for general objective functions, for bounded-degree functions, and for a restricted class of quadratizations. Our upper bounds are constructive, thus yielding new quadratization procedures. Finally, we completely characterize all ``minimal'' quadratizations of negative monomials. [less ▲]

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See detailQuadratic reformulations of nonlinear binary optimization problems
Crama, Yves ULiege

Conference (2016, December 14)

Detailed reference viewed: 9 (0 ULiège)
See detailA class of valid inequalities for multilinear 0-1 optimization problems
Rodriguez Heck, Elisabeth ULiege; Crama, Yves ULiege

Conference (2016, December 14)

Detailed reference viewed: 18 (1 ULiège)
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See detailBerge-acyclic multilinear 0-1 optimization problems
Buchheim, Christoph; Crama, Yves ULiege; Rodriguez Heck, Elisabeth ULiege

E-print/Working paper (2016)

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See detailLarge neighborhood search for multi-trip vehicle routing
François, Véronique ULiege; Arda, Yasemin ULiege; Crama, Yves ULiege et al

in European Journal of Operational Research (2016), 255(2), 422-441

We consider the multi-trip vehicle routing problem, in which each vehicle can perform several routes during the same working shift to serve a set of customers. The problem arises when customers are close ... [more ▼]

We consider the multi-trip vehicle routing problem, in which each vehicle can perform several routes during the same working shift to serve a set of customers. The problem arises when customers are close to each other or when their demands are large. A common approach consists of solving this problem by combining vehicle routing heuristics with bin packing routines in order to assign routes to vehicles. We compare this approach with a heuristic that makes use of specific operators designed to tackle the routing and the assignment aspects of the problem simultaneously. Two large neighborhood search heuristics are proposed to perform the comparison. We provide insights into the configuration of the proposed algorithms by analyzing the behavior of several of their components. In particular, we question the impact of the roulette wheel mechanism. We also observe that guiding the search with an objective function designed for the multi-trip case is crucial even when exploring the solution space of the vehicle routing problem. We provide several best known solutions for benchmark instances. [less ▲]

Detailed reference viewed: 93 (33 ULiège)