1,721,043 research outputs found
Agent scheduling in a multiskill call center
No full textThis is a summary of the author’s PhD thesis, supervised by Pierre L’Ecuyer and Roberto Musmanno and defended on 21 February 2008 at the Università della Calabria. The thesis is written in English and is available from the author upon request. This work deals with the comparison of simulation-based algorithms for solving the agents scheduling problem in a multiskill call center minimizing their costs under service levels constraints. A solution approach, combining simulation, with integer or linear programming, and cut generation, is proposed. Considering realistic problems, it performs better than the two-step approach proposed in the literature. It is also shown that a randomized search, extending the one defined for the single-period staffing problem in Avramidis et al. [IIE Trans (in press), 2008], yields highly suboptimal solutions. Finally, an extension of the cutting plane method to directly control the probability on the customers abandonments is designed
A pick-up and delivery problem with time windows by electric vehicles
No full textIn the pick-up and delivery problem with time windows (PDPTW), each transportation service is delivered, from an origin to a destination, satisfying both the time windows and the precedence constraints. This paper addresses the related vehicle routing problem by using only electric vehicles (EVs) and by introducing the recharging stations (RSs). The problem is formulated as a multi-objective mixed integer linear model for minimising the total travel distance, the total cost for the EVs used and the total penalty cost for the unsatisfied time windows. In addition, length constraints on the routes are imposed in order to include several aspects such as the limited availability of the RSs. The weighted sum method is adopted and, to properly set the weights, three methods, derived from the analytical hierarchical process, are compared. Computational experiments on some instances are carried out, in order to assess the behaviour of our approach in terms of solution quality
Comparing matheuristic approaches for the Electric Vehicle Routing Problem with Time Windows
No full textDamped Techniques for the Limited Memory BFGS Method for Large-Scale Optimization
No full textThis paper is aimed to extend a certain damped technique, suitable for the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method, to the limited memory BFGS method in the case of the large-scale unconstrained optimization. It is shown that the proposed technique maintains the global convergence property on uniformly convex functions for the limited memory BFGS method. Some numerical results are described to illustrate the important role of the damped technique. Since this technique enforces safely the positive definiteness property of the BFGS update for any value of the steplength, we also consider only the first Wolfe–Powell condition on the steplength. Then, as for the backtracking framework, only one gradient evaluation is performed on each iteration. It is reported that the proposed damped methods work much better than the limited memory BFGS method in several cases
An approximate epsilon-constraint method for a multi-objective job scheduling in the cloud
No full textCloud computing is a hybrid model that provides both hardware and software resources through computer networks. Data services (hardware) together with their functionalities (software) are hosted on web servers rather than on single computers connected by networks. Through a device (e.g., either a computer or a smartphone), a browser and an Internet connection, each user accesses a cloud platform and asks for specific services. For example, a user can ask for executing some applications (jobs) on the machines (hosts) of a cloud infrastructure. Therefore, it becomes significant to provide optimized job scheduling approaches suitable to balance the workload distribution among hosts of the platform. In this paper, a multi-objective mathematical formulation of the job scheduling problem in a homogeneous cloud computing platform is proposed in order to optimize the total average waiting time of the jobs, the average waiting time of the jobs in the longest working schedule (such as the makespan) and
the required number of hosts. The proposed approach is based on an approximate ε-constraint method, tested on a set of instances and compared with the weighted sum (WS) method. The computational results highlight that our approach outperforms the WS method in terms of a number of non-dominated solution
Pervasive Cloud Computing Technologies: Future Outlooks and Interdisciplinary Perspectives
No full textTechnology trends may come and go, but cloud computing technologies have been gaining consideration in the commercial world due to its ability to provide on-demand access to resources, control the software environment, and supplement existing systems. Pervasive Cloud Computing Technologies: Future Outlooks and Interdisciplinary Perspectives explores the latest innovations with cloud computing and the impact of these new models and technologies. This book will present case studies and research on the future of cloud computing technologies and its ability to increase connectivity of various entities of the world. It is an essential resource for technology practitioners, engineers, managers, and academics aiming to gain the knowledge of these novel and pervasive technologies
Efficiently routing a fleet of autonomous vehicles in a real-time ride-sharing system
Full text linkThe advent of new communication technologies (e.g., smartphone) and autonomous vehicles (AVs) is enabling real-time ride-sharing systems where the travel requests arrives in the system on very short notice or even en-route, i.e., when AVs are already serving other users. Each request specifies an origin, a destination and a time window of pick-up, and must be immediately either accepted or rejected. Each request accepted must be assigned to an AV and both scheduled and inserted in its route considering the other possible requests already assigned to the same AV. In a lexicographic way, first we want to maximize the total number of new requests accepted, then we want to minimize the total traveled distance and finally, the total time of serving the requests. The problem is formulated as a Mixed Integer Linear Program and solved by a rolling horizon approach (MILP-RH). To efficiently address medium/large-sized instances, a rolling horizon Local Search (RHLS) is also designed, with moves properly tailored for the problem Numerical comparisons show that, on both the small-sized and some medium-sized instances, the RHLS outperforms the MILP-RH concerning the total computational time. Instead, on some medium-sized and on the large-sized instances, the RHLS is the only viable method since the MILP-RH is not able to even find a feasible solution in the given time limit. A sensitivity analysis on possible variation of some parameters is also performed deriving some useful managerial insights
Damped Techniques for the Limited Memory BFGS Method for LargeScale Optimization
No full textThis paper is aimed to extend a certain damped technique, suitable for the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method, to the limited memory BFGS method in the case of the large-scale unconstrained optimization. It is shown that the proposed technique maintains the global convergence property on uniformly convex functions for the limited memory BFGS method. Some numerical results are described to illustrate the important role of the damped technique. Since this technique enforces safely the positive definiteness property of the BFGS update for any value of the steplength, we also consider only the first Wolfe–Powell condition on the steplength. Then, as for the backtracking framework, only one gradient evaluation is performed on each iteration. It is reported that the proposed damped methods work much better than the limited memory BFGS method in several cases
Web services for healthcare management
No full textNowadays, Health Care Organizations (HCOs) are interested in defining methodologies of Information Technology (IT) for providing high quality services at minimum cost. Through modern software and hardware, they can process data and manage the three important phases: diagnosis, prognosis, and therapy. In this scenario, Web Technologies (WTs) can: provide advanced Information Systems that combine software applications; offer a heterogeneous connectivity to users; allow costs reduction; improve the delivery of the services; guarantee an interactive support of the doctors, interconnectivity between the HCOs, and effective information sharing. In this chapter, first it is described how to provide the services of a HCO through the WTs, and then it is shown how Operations Research makes it more effective, to deal with, for example, clinical data classification problem, clinical predictions, clinical what-if analysis, and Web services composition process
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