Paolo Detti

Load Scheduling for Household Energy Consumption Optimization

This paper concerns the problem of optimally scheduling a set of appliances at the end-user premises. In the context of electricity smart grids, the electric energy fee varies over time and the user may receive a reward from an energy aggregator if he/she modifies his/her consumption profile during certain time intervals. The problem is to schedule the operation of the appliances taking into account overall costs, climatic comfort level and timeliness. We devise a MILP model and a heuristic algorithm accounting for a typical household user. Several numerical simulation results are reported, showing that the problem can be efficiently solved in real-life instances.

Centralized Radio Resource Allocation for OFDMA Cellular Systems

Efficient resource allocation in cellular OFDMA systems envisages the assignment of the number of sub-carriers and the relative transmission format on the basis of the experimented link quality. In this way, a higher number of sub-carriers with low per-carrier cshould be assigned to users at cell border. This strategy has already proved its efficiency in the single-cell scenario, while no study has been provided in the multi-cell scenario with reuse factor equal to one, i.e., in presence of severe interference conditions. In this paper we propose an optimum centralized radio resource allocator for the multi-cell scenario of an OFDMA cellular system which allows to highly outperform iterative decentralized allocation strategies based on local optimization criteria. The proposed scheme is characterized by huge implementation complexity, and, hence, it can be hardly implemented in the real world. However, it can help the system designer in catching the essence of interference limitations in OFDMA cellular systems, thus allowing the elaboration of efficient heuristic decentralized approaches. As an example, we prove that the sub-carrier transmission format adaptation is not useful in a multi-cell scenario. This is because users at cell border tends to consume the most of the resources (i.e., they are assigned the most of sub-carriers), thus producing interference for the neighbor cells over a large set of sub-carriers. Hence, since in this case neighbor cells are forced to use those (few) sub-carriers which experiment low interference, the diversity gain tends to be missed.

Set-up coordination between two stages of a supply chain

In the material flow of a plant, parts are processed in batches, each having two distinct attributes, say shape and color. In one department, a set-up occurs every time the shape of the new batch is different from the previous one. In a downstream department, there is a set-up when the color of the new batch is different from the previous one. Since a unique sequence of batches must be established, the problem consists in finding such a common sequence optimizing an overall utility index. Here we consider two indices, namely the total number of set-ups and the maximum number of set-ups between the two departments. Both problems are shown to be NP-hard. An efficient heuristic approach is presented for the first index which allows to solve a set of real-life instances and performs satisfactorily on a large sample of experimental data.

Radio resource allocation problems for OFDMA cellular systems

Orthogonal frequency division multiple-access (OFDMA) manages to efficiently exploit the inherent multi-user diversity of a cellular system by performing dynamic resource allocation. Radio resource allocation is the technique that assigns to each user in the system a subset of the available radio resources (mainly power and bandwidth) according to a certain optimality criterion on the basis of the experienced link quality. In this paper we address the problem of resource allocation in the downlink of a multi-cellular OFDMA system. The allocation problem is formulated with the goal of minimizing the transmitted power subject to individual rate constraint for each user. Exact and heuristic algorithms are proposed for the both the single-cell and the multi-cell scenario. In particular, we show that in the single-cell scenario the allocation problem can be efficiently solved following a network flow approach. In the multi-cell scenario we assume that all cells use the same frequencies and therefore the allocation problem is complicated by the presence of strong multiple access interference. We prove that the problem is strongly NP-hard, and we present an exact approach based on an MILP formulation. We also propose two heuristic algorithms designed to be simple and fast. All algorithms are tested and evaluated through an experimental campaign on simulated instances. Experimental results show that, although suboptimal, a Lagrangian-based heuristic consisting in solving a series of minimum network cost flow problems is attractive for practical implementation, both for the quality of the solutions and for the small computational times.

Appliance operation scheduling for electricity consumption optimization

This paper concerns the problem of optimally scheduling a set of appliances at the end-user premises. The users energy fee varies over time, and moreover, in the context of smart grids, the user may receive a reward from an energy aggregator if he/she reduces consumption during certain time intervals. In a household, the problem is to decide when to schedule the operation of the appliances, in order to meet a number of goals, namely overall costs, climatic comfort level and timeliness. We devise a model accounting for a typical household user, and present computational results showing that it can be efficiently solved in real-life instances.

Message Passing Resource Allocation for the Uplink of Multi-Carrier Multi-Format Systems

We propose two novel distributed resource allocation (RA) schemes for the uplink of a cellular multi-carrier multi-format system based on the message passing (MP) technique. In the proposed approaches each transmitter iteratively sends and receives information messages to/from the base station with the goal of achieving an optimal RA strategy. The exchanged messages are the solution of small distributed allocation problems. Hence, despite the NP-hardness of the original RA problem, they distribute the computational effort in the cell among all the transmitters and the base station. Specifically, the first algorithm combines MP with a dynamic programming formula solved at each step, while the second method initially solves to optimality a simplified single-format RA via MP, and eventually performs format allocation to satisfy the rate constraints. Compared to alternatives, numerical results assess the validity of MP-based schemes both in terms of efficiency and complexity.

Minimizing and balancing setups in a serial production system

This paper addresses a problem arising in the coordination between two consecutive manufacturing departments of a production system, in which parts are processed in batches, and each batch is characterized by two distinct attributes. Due to limited interstage buffering between the two stages, the two departments have to follow the same batch sequence. In the first department, a setup occurs every time the first attribute of the new batch is different from the previous one. In the downstream department, there is a setup when the second attribute of the new batch changes. The problem consists of finding a common batch sequence optimizing some global utility index. Here we propose a metaheuristic approach to a bi-criteria version of the problem considering two indices, namely the total number of setups paid for by the two departments and the maximum number of setups paid for by either department.

A linear algorithm for the Hamiltonian completion number of the line graph of a tree

Abstract Given a graph G=(V,E) , HCN(L(G)) is the minimum number of edges to be added to its line graph L(G) to make L(G) Hamiltonian. This problem is known to be NP-hard for general graphs, whereas an O (|V| 5 ) algorithm exists when G is a tree. In this paper a linear algorithm for finding HCN(L(G)) when G is a tree is proposed.

Message Passing Resource Allocation for the Uplink of Multicarrier Systems

We propose a novel distributed resource allocation scheme for the up-link of a cellular multi-carrier system based on the message passing (MP) algorithm. In the proposed approach each transmitter iteratively sends and receives information messages to/from the base station with the goal of achieving an optimal resource allocation strategy. The exchanged messages are the solution of small distributed allocation problems. To reduce the computational load, the MP problems at the terminals follow a dynamic programming formulation. The advantage of the proposed scheme is that it distributes the computational effort among all the transmitters in the cell and it does not require the presence of a central controller that takes all the decisions. Numerical results show that the proposed approach is an excellent solution to the resource allocation problem for cellular multi-carrier systems.

A planning and routing model for patient transportation in health care

Abstract In this paper, a problem concerning both the planning of health care services and the routing of vehicles, for patients transportation is addressed. An integrated approach, based on the column generation technique, is proposed to solve the planning and routing problem. Preliminary results on real data show the effectiveness of the proposed approach.