The multi-period pp-center problem with time-dependent travel times

This paper deals with an extension of the $p$-center problem, in which arc traversal times vary over time, and facilities are mobile units that can be relocated multiple times during the planning horizon. We investigate the relationship between this problem and its single-period counterpart. We also derive some properties and a special case. The insight gained with this analysis is then used to devise a two-stage heuristic. Computational results on instances based on the Paris (France) road graph indicate that the algorithm is capable of determining good-quality solutions in a reasonable execution time

Dynamic Priority Rules for Combining On-Demand Passenger Transportation and Transportation of Goods

Urban on-demand transportation services are booming, in both passenger transportation and the transportation of goods. The types of service differ in timeliness and compensation and, until now, providers operate larger fleets separately for each type of service. While this may ensure sufficient resources for lucrative passenger transportation, the separation also leaves consolidation potentials untapped. In this paper, we propose combining both services in an anticipatory way that ensures high passenger service rates while simultaneously transporting a large number of goods. To this end, we introduce a dynamic priority policy that uses a time-dependent percentage of vehicles mainly to serve passengers. To find effective time-dependent parametrizations given a limited number of runtime-expensive simulations, we apply Bayesian Optimization. We show that our anticipatory policy increases revenue and service rates significantly while a myopic combination of service may actually lead to inferior performance compared to using two separate fleets

Long-Term Results of the FOLL05 Trial Comparing R-CVP Versus R-CHOP Versus R-FM for the Initial Treatment of Patients With Advanced-Stage Symptomatic Follicular Lymphoma

Purpose The FOLL05 trial compared R-CVP (rituximab plus cyclophosphamide, vincristine, and prednisone) with R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) and R-FM (rituximab plus fludarabine and mitoxantrone) regimens without rituximab maintenance as initial therapy for patients with advanced-stage follicular lymphoma (FL). A previous analysis with a median follow-up of 34 months showed a superior 3-year time to treatment failure, the primary study end point, with R-CHOP and R-FM versus R-CVP and showed R-CHOP to have a better risk-benefit ratio in terms of toxicity than R-FM. We report a post hoc analysis of this trial after a median follow-up of 7 years. Patients and Methods Of the 534 enrolled patients, 504 were evaluable. At the time of analysis, the median follow-up was 84 months (range, 1 to 119 months). Results The 8-year time to treatment failure and progression-free survival rates were 44% (95% CI, 39% to 49%) and 48% (95% CI, 43% to 53%), respectively. The hazard ratio for progression-free survival adjusted by FL International Prognostic Index 2 versus R-CVP was 0.73 for R-CHOP (95% CI, 0.54 to 0.98; P = .037) and 0.67 for R-FM (95% CI, 0.50 to 0.91; P = .009). The 8-year overall survival (OS) rate was 83% (95% CI, 79% to 87%), with no significant differences among study arms. Overall, we observed a higher risk of dying as a result of causes unrelated to lymphoma progression with R-FM versus R-CVP. Conclusion With an 83% 8-year OS rate, long-term follow-up of the FOLL05 trial confirms the favorable outcome of patients with advanced-stage FL treated with immunochemotherapy. The three study arms had similar OS but different activity and toxicity profiles. Patients initially treated with R-CVP had a higher risk of lymphoma progression compared with those receiving R-CHOP, as well as a higher risk of requiring additional therapy

Estimating travel and service times for automated route planning and service certification in municipal waste management

Nowadays, route planning algorithms are commonly used to generate detailed work schedules for solid waste collection vehicles. However, the reliability of such schedules relies heavily on the accuracy of a number of parameters, such as the actual service time at each collection location and the traversal times of the streets (which depend on the specific day of the week and the time of day). In this paper, we propose an automated classification and estimation algorithm that, based on Global Positioning System data collected by the fleet, estimates such parameters in a timely and accurate fashion. In particular, our approach is able to classify automatically events like stops due to traffic jams, stops at traffic lights and stops at collection sites. The system can also be used for automated fleet supervision and in order to notify on a web site whether certain services have been actually provided on a certain day, thus making waste management more accountable to citizens. An experimentation carried out in an Italian municipality shows the advantages of our approach

The impact of an efficient collection sites location on the zoning phase in municipal solid waste management

In this paper, we study two decisional problems arising when planning the collection of solid waste, namely the location of collection sites (together with bin allocation) and the zoning of the service territory, and we assess the potential impact that an efficient location has on the subsequent zoning phase. We first propose both an exact and a heuristic approach to locate the unsorted waste collection bins in a residential town, and to decide the capacities and characteristics of the bins to be located at each collection site. A peculiar aspect we consider is that of taking into account the compatibility between the different types of bins when allocating them to collection areas. Moreover, we propose a fast and effective heuristic approach to identify homogeneous zones that can be served by a single collection vehicle. Computational results on data related to a real-life instance show that an efficient location is fundamental in achieving consistent monetary savings, as well as a reduced environmental impact. These reductions are the result of one vehicle less needed to perform the waste collection operations, and an overall traveled distance reduced by about 25% on the average

Optimizing a waste collection system with solid waste transfer stations

In recent years, stricter environmental regulations, as well as an increased public concern, have progressively forced new landfills to be located more and more away from urban centers. This has stimulated the use of solid waste transfer stations, where the solid waste is transferred from small collection vehicles to large transportation vehicles. In this paper, we tackle the problem of determining the routes for both collection and transportation vehicles, as well as their synchronization at the transfer stations. We divide the problem into two phases and propose an exact approach utilizing a mathematical formulation, as well as a constructive heuristic and a matheuristic for the first phase, and a heuristic approach for the second phase. Computational results show that the approach combining the matheuristic for the collection phase with the heuristic for the transportation phase is able to achieve consistent reductions in terms of number of collection vehicles needed

Scheduled penalty variable neighborhood search

For many NP-hard combinatorial optimization problems, the existence of constraints complicates the implementation of a heuristic search procedure. In this paper, we propose a general heuristic framework that extends the well known Variable Neighborhood Search algorithm to include dynamic constraint penalization. We specifically focus on what are known as scheduled penalty methods and call the new algorithm scheduled-penalty Variable Neighborhood Search. The proposed method is tested on two well known constrained combinatorial optimization problems, namely the Traveling Salesman Problem with Time Windows and the Orienteering Problem with Time Windows. Our results demonstrate the effectiveness of the proposed algorithm, which is capable of producing high-quality solutions to the well known benchmark problems chosen in this paper with only minimal problem-specific tailoring of the general algorithm. Moreover, we introduce new best known solutions for some instances from the orienteering problem with time windows literature

Simultaneous personnel and vehicle shift scheduling in the waste management sector

Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the definition of shift schedules for both personnel and vehicles. This activity has a great incidence on the tactical and operational cost for companies. In this paper, we propose an integer programming model to find an optimal solution to the integrated problem. The aim is to determine optimal schedules at minimum cost. Moreover, we design a fast and effective heuristic to face large-size problems. Both approaches are tested on data from a real-world case in Southern Italy and compared to the current practice utilized by the company managing the service, showing that simultaneously solving these problems can lead to significant monetary savings