Robustness of solutions to the capacitated facility location problem with uncertain demand

We investigate the properties of robust solutions of the Capacitated Facility Location Problem with uncertain demand. We show that the monotonic behavior of the price of robustness is not guaranteed, and therefore that one cannot discriminate among alternative robust solutions by simply relying on the trade-off price-vs-robustness. Furthermore, we report a computational study on benchmark instances from the literature and on instances derived from a real-world application, which demonstrates the validity in practice of our findings

UniALT for regular language contrained shortest paths on a multi-modal transportation network

Shortest paths on road networks can be efficiently calculated using Dijkstra\u27s algorithm (D). In addition to roads, multi-modal transportation networks include public transportation, bicycle lanes, etc. For paths on this type of network, further constraints, e.g., preferences in using certain modes of transportation, may arise. The regular language constrained shortest path problem deals with this kind of problem. It uses a regular language to model the constraints. The problem can be solved efficiently by using a generalization of Dijkstra\u27s algorithm (D_RegLC). In this paper we propose an adaption of the speed-up technique uniALT, in order to accelerate D_RegLC. We call our algorithm SDALT. We provide experimental results on a realistic multi-modal public transportation network including time-dependent cost functions on arcs. The experiments show that our algorithm performs well, with speed-ups of a factor 2 to 20

A Column Generation Based Heuristic for the Multicommodity-ring Vehicle Routing Problem

AbstractWe study a new routing problem arising in City Logistics. Given a ring connecting a set of urban distribution centers (UDCs) in the outskirts of a city, the problem consists in delivering goods from virtual gates located outside the city to the customers inside of it. Goods are transported from a gate to a UDC, then either go to another UDC before being delivered to customers or are directly shipped from the first UDC. The reverse process occurs for pick-up. Routes are performed by electric vans and may be open. The objective is to find a set of routes that visit each customer and to determine ring and gates-UDC flows so that the total transportation and routing cost is minimized. We solve this problem using a column generation-based heuristic, which is tested over a set of benchmark instances issued from a more strategic location-routing problem

Efficient algorithms for the 2-Way Multi Modal Shortest Path Problem

7International audienceWe consider the 2-Way Multi Modal Shortest Path Problem (2WMMSPP). Its goal is tofi nd two multi modal paths with total minimal cost, an outgoing path and a return path. The main di fficulty lies in the fact that if a private car or bicycle is used during the outgoing path, it has to be picked up during the return path. The shortest return path is typically not equal to the shortest outgoing path as tra ffic conditions and timetables of public transportation vary throughout the day. In this paper we propose an e fficient algorithm based on bi-directional search and provide experimental results on a realistic multi modal transportation network

The multiple vehicle balancing problem

This paper deals with the multiple vehicle balancing problem (MVBP). Given a fleet of vehicles of limited capacity, a set of vertices with initial and target inventory levels and a distribution network, the MVBP requires to design a set of routes along with pickup and delivery operations such that inventory is redistributed among the vertices without exceeding capacities, and routing costs are minimized. The MVBP is NP\u2010hard, generalizing several problems in transportation, and arising in bike\u2010sharing systems. Using theoretical properties of the problem, we propose an integer linear programming formulation and introduce strengthening valid inequalities. Lower bounds are computed by column generation embedding an ad\u2010hoc pricing algorithm, while upper bounds are obtained by a memetic algorithm that separate routing from pickup and delivery operations. We combine these bounding routines in both exact and matheuristic algorithms, obtaining proven optimal solutions for MVBP instances with up to 25 stations

Building and Application of Cardiopulmonary Bypass Model in Rats

To build a cardiopulmonary bypass model in rats, and research the feasibility. Method Cardiopulmonary bypass was built in 10 adult male SD rats of clean grade through intubation in jugular vein, caudal artery, and femoral artery, and bypass was sustained for 60 min at the flow rate of 100ml/(kg•min) to monitor heart rate, blood pressure, blood gas, and electrolyte. Result Puncture succeeded in all the 20 rats, and cardiopulmonary bypass was finished under given conditions. Conclusion The model has the following advantages, economical efficiency, simplicity, minimal invasion, cardiopulmonary bypass parameter setting similar to that of clinical trail, high rate of success. Thus, it is reliable for researching pathological and physiological changes after cardiopulmonary bypass and evaluating therapeutic strategy

An exact algorithm for the static rebalancing problem arising in bicycle sharing systems

Bicycle sharing systems can significantly reduce traffic, pollution, and the need for parking spaces in city centers. One of the keys to success for a bicycle sharing system is the efficiency of rebalancing operations, where the number of bicycles in each station has to be restored to its target value by a truck through pickup and delivery operations. The Static Bicycle Rebalancing Problem aims to determine a minimum cost sequence of stations to be visited by a single vehicle as well as the amount of bicycles to be collected or delivered at each station. Multiple visits to a station are allowed, as well as using stations as temporary storage. This paper presents an exact algorithm for the problem and results of computational tests on benchmark instances from the literature. The computational experiments show that instances with up to 60 stations can be solved to optimality within 2 hours of computing time

The static bicycle relocation problem with demand intervals

This study introduces the Static Bicycle Relocation Problem with Demand Intervals (SBRP-DI), a variant of the One Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP). In the SBRP-DI, the stations are required to have an inventory of bicycles lying between given lower and upper bounds and initially have an inventory which does not necessarily lie between these bounds. The problem consists of redistributing the bicycles among the stations, using a single capacitated vehicle, so that the bounding constraints are satisfied and the repositioning cost is minimized. The real-world application of this problem arises in rebalancing operations for shared bicycle systems. The repositioning subproblem associated with a fixed route is shown to be a minimum cost network problem, even in the presence of handling costs. An integer programming formulation for the SBRP-DI are presented, together with valid inequalities adapted from constraints derived in the context of other routing problems and a Benders decomposition scheme. Computational results for instances adapted from the 1-PDTSP are provided for two branch-and-cut algorithms, the first one for the full formulation, and the second one with the Benders decomposition