Author
Amar Oukil
Other affiliations: HEC Montréal, Lancaster University
Bio: Amar Oukil is an academic researcher from Sultan Qaboos University. The author has contributed to research in topics: Data envelopment analysis & Ranking. The author has an hindex of 14, co-authored 33 publications receiving 555 citations. Previous affiliations of Amar Oukil include HEC Montréal & Lancaster University.
Papers
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TL;DR: It is shown that each stage of the proposed methodology enhances discrimination among DMUs while offering more flexibility to the decision process.
65 citations
TL;DR: The outcome shows the great potential of such an approach for degenerate instances of the multiple-depot vehicle scheduling problem, and combines column generation, preprocessing variable fixing, and stabilization.
65 citations
TL;DR: In this article, the authors evaluated the performance of the hotel industry in the Sultanate of Oman through a two-stage data envelopment analysis (DEA) procedure, in which DEA-bootstrap is used to estimate point and interval efficiency ratios of the hotels, and a truncated regression model based on the double bootstrapping procedure of Simar & Wilson (2007) is implemented to identify potential sources of hotels' operational inefficiency.
62 citations
01 Oct 2004
TL;DR: In this paper, column generation, preprocessing variable fixing, and stabilization are combined to solve the linear relaxation of the multiple-depot vehicle scheduling problem (MDVSP) for degenerate instances.
Abstract: Column generation has proven to be efficient in solving the linear programming relaxation of large scale instances of the multiple-depot vehicle scheduling problem (MDVSP). However difficulties arise when the instances are highly degenerate. Recent research has been devoted to accelerate column generation while remaining within the linear programming framework. This paper presents an efficient approach to solve the linear relaxation of the MDVSP. It combines column generation, preprocessing variable fixing, and stabilization. The outcome shows the great potential of such an approach for degenerate instances.
57 citations
TL;DR: This paper uses the advantage of multiple optimal solutions, be in the cases of efficient and/or inefficient DMUs, to integrate both the first and second-order voices of all DMUs and proposes a most appreciative cross-efficiency DEA method.
53 citations
Cited by
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TL;DR: This classification is the first to categorize the articles of the VRP literature to this level of detail and is based on an adapted version of an existing comprehensive taxonomy.
800 citations
TL;DR: This paper discusses the modeling approaches for different kinds of vehicle scheduling problems and gives an up-to-date and comprehensive overview on the basis of a general problem definition.
Abstract: The vehicle scheduling problem, arising in public transport bus companies, addresses the task of assigning buses to cover a given set of timetabled trips with consideration of practical requirements such as multiple depots and vehicle types as well as further extensions. An optimal schedule is characterized by minimal fleet size and/or minimal operational costs. Various publications were released as a result of extensive research in the last decades on this topic. Several modeling approaches as well as specialized solution strategies were presented for the problem and its extensions. This paper discusses the modeling approaches for different kinds of vehicle scheduling problems and gives an up-to-date and comprehensive overview on the basis of a general problem definition. Although we concentrate on the presentation of modeling approaches, also the basic ideas of solution approaches are given.
232 citations
TL;DR: The CVRPSD can be formulated as a set partitioning problem and it is shown that the associated column generation subproblem can be solved using a dynamic programming scheme.
174 citations
TL;DR: Wang et al. as mentioned in this paper presented an equitable model for efficiency evaluation of decision-making units with undesirable outputs and introduced a technique for cross-efficiency evaluation considering undesirable outputs, and a ranking priority model was proposed considering the decision making units' intentions of pursuing the best ranking positions.
126 citations
TL;DR: In this article, an adaptive large-scale neighbourhood search heuristic for the CARP with stochastic demands is presented. But the authors do not consider the problem of garbage collection.
Abstract: The capacitated arc-routing problem with stochastic demands (CARPSD) is an extension of the well-known capacitated arc-routing problem (CARP) in which demands are stochastic. This leads to the possibility of route failures whenever the realized demand exceeds the vehicle capacity. This paper presents the CARPSD in the context of garbage collection. It describes an adaptive large-scale neighbourhood search heuristic for the problem. Computational results show the superiority of this algorithm over an alternative solution approach.
116 citations