Silvia Rismondo

A market-based multi-agent system model for decentralized multi-project scheduling

We consider a multi-project scheduling problem, where each project is composed of a set of activities, with precedence relations, requiring specific amounts of local and shared (among projects) resources. The aim is to complete all the project activities, satisfying precedence and resource constraints, and minimizing each project schedule length. The decision making process is supposed to be decentralized, with as many local decision makers as the projects. A multi-agent system model, and an iterative combinatorial auction mechanism for the agent coordination are proposed. We provide a dynamic programming formulation for the combinatorial auction problem, and heuristic algorithms for both the combinatorial auction and the bidding process. An experimental analysis on the whole multi-agent system model is discussed.

A tabu search approach for scheduling hazmat shipments

Vehicle routing and scheduling are two main issues in the hazardous material (hazmat) transportation problem. In this paper, we study the problem of managing a set of hazmat transportation requests in terms of hazmat shipment route selection and actual departure time definition. For each hazmat shipment, a set of minimum and equitable risk alternative routes from origin to destination points and a preferred departure time are given. The aim is to assign a route to each hazmat shipment and schedule these shipments on the assigned routes in order to minimize the total shipment delay, while equitably spreading the risk spatially and preventing the risk induced by vehicles traveling too close to each other. We model this hazmat shipment scheduling problem as a job-shop scheduling problem with alternative routes. No-wait constraints arise in the scheduling model as well, since, supposing that no safe area is available, when a hazmat vehicle starts traveling from the given origin it cannot stop until it arrives at the given destination. A tabu search algorithm is proposed for the problem, which is experimentally evaluated on a set of realistic test problems over a regional area, evaluating the provided solutions also with respect to the total route risk and length.

Hybrid genetic algorithm to approach the DARP in a demand responsive passenger service

Abstract In this work, we address a Demand Responsive Transport System capable of managing incoming transport demand using a solution architecture based on a two- stage algorithm to solve a Dial-a-Ride Problem instance. In the first stage, a constructive heuristic algorithm quickly provides a feasible solution to accept the incoming demand. The algorithm in the second stage is a specialized Hybrid Genetic Algorithm that attempts to improve the solution evaluated at the first stage by using the time between two consecutive transportation events.

A NEW MODEL FOR ACHIEVING VALUE ADDED GOALS IN A COLLABORATIVE INDUSTRIAL SCENARIO

Nowadays, at industrial research level, seems to be recognised that the Collaboration among firms is becoming a relevant and effective way of operating. For the enterprises rather than compete on costs it could be necessary increase the product/service value added; this goal could be effectively achieved by collaborating with other firms in the value chain.

Integrating Procurement, Production Planning, and Inventory Management Processes Through Negotiation Information

Negotiation is a basic process for the enterprise activities. In this paper we study the problem of creating a tool that allows a manufacturing enterprise to integrate the negotiation related to the procurement process with the production planning, and stock processes. We formulate the procurement problem as a reverse combinatorial auction, and we provide a new mathematical formulation that considers procurement, production, and stock costs.