Heuristics for a green orienteering problem

We address a routing problem where a vehicle with limited time, loading capacity and battery autonomy can optionally serve a set of customers, each providing a profit. Such a problem is of particular relevance both because of its practical implications in sustainable transportation and its use as a sub-problem in Green Vehicle Routing column generation algorithms. We propose a dynamic programming approach to obtain both primal and dual bounds to the value of the optimal solutions, a fast greedy heuristics and a very large scale neighbourhood search procedure

Inventory rebalancing in bike-sharing systems

We address an optimization problem arising in rebalancing operations of inventory levels in bike-sharing systems. Such systems are public services where bikes are available for shared use on a short term basis. To ensure the availability of bikes in each station and avoid disservices, the bike inventory level of each station must met a forecast value. This is achieved through the use of a fleet of vehicles moving bikes between stations. Our problem can be classified as a Split Pickup and Split Delivery Vehicle Routing Problem. We propose a formulation in which routes are decomposed in smaller structures and we exploit properties on the structure of the optimal solutions, to design an exact algorithm based on branch-and-price

A single machine on-time-in-full scheduling problem

A relevant feature in many production contexts is flexibility. This becomes a key issue, for instance, in the case of third-party cosmetics manufacturing [1]. There, the core business is the production of high quality, fully custom orders in limited batches. Competition is pushing companies to aggressive commercial policies, involving tight delivery dates. At the same time, the custom nature of the orders makes it impossible to keep materials in stock; lead times are always uncertain, often making release dates tight as well, and ultimately yielding unexpected peaks of production loads

Dynamic cloudlet assignment problem: A column generation approach

Major interest in network optimization is currently given to the integration of clusters of virtualization servers, also referred to as 'cloudlets', into mobile access networks for improved performance and reliability. Mobile access points (APs) are assigned (i.e., route their packets) to one or more cloudlets, with a cost in terms of latency for the users they provide connections to. Assignment of APs to cloudlet can be changed over time, with a cloudlet synchronization cost. We tackle the problem of the optimal assignment of APs to cloudlets over time, proposing dedicated mathematical models and column generation algorithms

Mathematical Programming Algorithms for Spatial Cloaking

We consider a combinatorial optimization problem for spatial information cloaking. The problem requires computing one or several disjoint arborescences on a graph from a predetermined root or subset of candidate roots, so that the number of vertices in the arborescences is minimized but a given threshold on the overall weight associated with the vertices in each arborescence is reached. For a single arborescence case, we solve the problem to optimality by designing a branch-and-cut exact algorithm. Then we adapt this algorithm for the purpose of pricing out columns in an exact branch-and-price algorithm for the multiarborescence version. We also propose a branch-and-price-based heuristic algorithm, where branching and pricing, respectively, act as diversification and intensification mechanisms. The heuristic consistently finds optimal or near optimal solutions within a computing time, which can be three to four orders of magnitude smaller than that required for exact optimization. From an application point of view, our computational results are useful to calibrate the values of relevant parameters, determining the obfuscation level that is achieved

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

Random Sampling and Machine Learning to Understand Good Decompositions

Motivated by its implications in the development of general purpose solvers for decomposable Mixed Integer Programs (MIP), we address a fundamental research question, that is to assess if good decomposition patterns can be consistently found by looking only at static properties of MIP input instances, or not. We adopt a data driven approach, devising a random sampling algorithm, considering a set of generic MIP base instances, and generating a large, balanced and well diversified set of decomposition patterns, that we analyze with machine learning tools. The use of both supervised and unsupervised techniques highlights interesting structures of random decompositions, as well as suggesting (under certain conditions) a positive answer to the initial question, triggering at the same time perspectives for future research. Keywords: Dantzig-Wolfe Decomposition, Machine Learning, Random Sampling

Neighborhood based heuristics for a two-level hierarchical location problem with modular node capacities

In many telecommunication network architectures a given set of client nodes must be served by different kinds of facility, which provide di fferent services and have diff erent capabilities. Such facilities must be located and dimensioned in the design phase. We tackle a particular location problem in which two sets of facilities, mid level and high level, have to be located. Different devices can be installed in each mid level facility, providing diff erent capacities at di fferent costs. The assignment of clients to facilities and of facilities to higher level entities must be optimized, as well. We propose a heuristic approach, based on very large scale neighborhood search, to tackle the problem, in which both ad-hoc algorithms and general purpose solvers are applied to explore the search space. We report on experimental results using datasets of instances from the literature. These experiments show that the approach is promising and that Integer Linear Programming based neighborhoods are significantly effective

Molecular dynamics of electrosprayed water nanodroplets containing sodium bis(2-ethylhexyl)sulfosuccinate

The behavior of aqueous solutions of sodium bis(2-ethylhexyl)sulfosuccinate (AOTNa) subject to electrospray ionization (ESI) has been investigated by molecular dynamics (MD) simulations at three temperatures (350, 500 and 800 K). We consider several types of water nanodroplets containing AOTNa molecules and composed of a fixed number of water molecules (1000), N0 AOT AOT anions (N0 AOT = 0, 5, 10) and N0 Na sodium ions (N0 Na = 0, 5, 10, 15, 20): in a short time scale (less than 1 ns), the AOTNa molecules, initially forming direct micelles in the interior of the water nanodroplets, are observed in all cases to diffuse nearby the nanodroplet surface, so that the hydrophilic heads and sodium ions become surrounded by water molecules, whereas the alkyl chains lay at the droplet surface. Meanwhile, evaporation of water molecules and of solvated sodium ions occurs, leading to a decrease of the droplet size and charge. At 350 K, no ejection of neutral or charged surfactant molecules is observed, whereas at 500 K, some fragmentation occurs, and at 800 K, this event becomes more frequent. The interplay of all these processes, which depend on the values of temperature, N0 AOT and N0 Na eventually leads to anhydrous charged surfactant aggregates with prevalence of monocharged ones, in agreement with experimental results of ESI mass spectrometry. The quantitative analysis of theMD trajectories allows to evidencemolecular details potentially useful in designing future ESI experimental conditions

Mobile Edge Cloud Network Design Optimization

Major interest is currently given to the integration of clusters of virtualization servers, also referred to as 'cloudlets' or 'edge clouds', into the access network to allow higher performance and reliability in the access to mobile edge computing services. We tackle the edge cloud network design problem for mobile access networks. The model is such that the virtual machines (VMs) are associated with mobile users and are allocated to cloudlets. Designing an edge cloud network implies first determining where to install cloudlet facilities among the available sites, then assigning sets of access points, such as base stations to cloudlets, while supporting VM orchestration and considering partial user mobility information, as well as the satisfaction of service-level agreements. We present link-path formulations supported by heuristics to compute solutions in reasonable time. We qualify the advantage in considering mobility for both users and VMs as up to 20% less users not satisfied in their SLA with a little increase of opened facilities. We compare two VM mobility modes, bulk and live migration, as a function of mobile cloud service requirements, determining that a high preference should be given to live migration, while bulk migrations seem to be a feasible alternative on delay-stringent tiny-disk services, such as augmented reality support, and only with further relaxation on network constraints