Andrea Attanasio

Parallel Tabu search heuristics for the dynamic multi-vehicle dial-a-ride problem

In the Dial-a-Ride problem (DARP) users specify transportation requests between origins and destinations to be served by vehicles. In the dynamic DARP, requests are received throughout the day and the primary objective is to accept as many requests as possible while satisfying operational constraints. This article describes and compares a number of parallel implementations of a Tabu search heuristic previously developed for the static DARP, i.e., the variant of the problem where all requests are known in advance. Computational results show that the proposed algorithms are able to satisfy a high percentage of user requests.

Auction algorithms for decentralized parallel machine scheduling

Computational grids are highly complex distributed systems (involving multiple organizations with different goals and policies) which aim at providing computing services without the users need to know the location and features of the required resources. A key issue in managing and scheduling grid resources is the coordination among multiple administrative domains. In this paper, we present a preliminary study which aims at developing auction mechanisms for decentralized scheduling which exhibit minimal communication overhead and an efficient usage of resources.

Real-Time Fleet Management At Ecourier Ltd

In this chapter we describe an innovative real-time fleet management system designed and implemented for eCourier Ltd (London, UK) for which patents are pending in the United States and elsewhere. This paper describes both the business challenges and benefits of the implementation of a real-time fleet management system (with reference to empirical metrics such as courier efficiency, service times, and financial data), as well as the theoretical and implementation challenges of constructing such a system. In short, the system dramatically reduces the requirements of human supervisors for fleet management, improves service and increases courier efficiency. We first illustrate the overall architecture, then depict the main algorithms, including the service territory zoning methodology, the travel time forecasting procedure and the job allocation heuristic

Integrated Shipment Dispatching and Packing Problems: a Case Study

In this paper we examine a consolidation and dispatching problem motivated by a multinational chemical company which has to decide routinely the best way of delivering a set of orders to its customers over a multi-day planning horizon. Every day the decision to be made includes order consolidation, vehicle dispatching as well as load packing into the vehicles. We develop a heuristic based on a cutting plane framework, in which a simplified Integer Linear Program (ILP) is solved to optimality. Since the ILP solution may correspond to a infeasible loading plan, a feasibility check is performed through a tailored heuristic for a three-dimensional bin packing problem with side constraints. If this test fails, a cut able to remove the infeasible solution is generated and added to the simplified ILP. Then the procedure is iterated. Computational results show that our procedure allows achieving remarkable cost savings.

Operations research methods for resource management and scheduling in a computational grid: a survey

Computational grids are emerging as the new generation computing paradigm for tackling large scale hard problems in a wide range of scientific fields. Grids are highly complex distributed systems (involving multiple organizations with different goals and policies) which aim at providing computing services without the users need to know the location and features of the required resources. While the current and previous research efforts have been mainly concentrated on architectures and protocols, this paper deals with quantitative methods for grid resource management. In particular, three main issues are considered: performance forecasting, local scheduling (i.e., job scheduling within a single administrative domain) and distributed mechanisms for coordinating grid resources within several administrative domains. For each such a topic, the current literature is reviewed and new research avenues are highlighted.

A general distributed framework based on Iterated Local Search

Some optimization problems are too complex to be solved exactly, using specific software tools. For this reason, in many cases it is more convenient to define and design a heuristic procedure even though the final solution is generally sub-optimal. One of the most promising approaches in the traditional computing environment is the Iterated Local Search method. It is based on an exploration of the neighbor of the current solution and its performance is estimated to be very high for a large number of problems. The main drawback of the approach could be the required computational time, in particular when the neighbor to be explored becomes too large. We propose a general distributed framework, based on Iterated Local Search, and we show a concrete application in logistics, related to the optimal assignment of products to storage locations in a warehouse.