Alessandro Agnetis

Multi-agent single machine scheduling

We consider the scheduling problems arising when several agents, each owning a set of nonpreemptive jobs, compete to perform their respective jobs on one shared processing resource. Each agent wants to minimize a certain cost function, which depends on the completion times of its jobs only. The cost functions we consider in this paper are maximum of regular functions (associated with each job), number of late jobs and total weighted completion time. The different combinations of the cost functions of each agent lead to various problems, whose computational complexity is analysed in this paper. In particular, we investigate the problem of finding schedules whose cost for each agent does not exceed a given bound for each agent.

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.

Scheduling no-wait robotic cells with two and three machines

Abstract A no-wait robotic cell is an automated m -machine flow shop in which one robot is used to move the parts from a machine to the next, as well as between the machines and the input/output devices. Parts are not allowed to wait, either on a machine or on the robot. The problem is to sequence the parts and, concurrently, schedule the robot moves in order to maximize productivity. In the two-machine case, we show that the problem is solvable in time O( n log n ) by reducing it to the classical two-machines no-wait flow shop. For the three-machine case and identical parts, it is shown that it is sufficient to consider robot move cycles in which all the machines are visited once or twice.

Part sequencing in three-machine no-wait robotic cells

A no-wait robotic cell is an automated flow shop in which a robot is used to move the parts from a machine to the next. Parts are not allowed to wait. We analyze the complexity of the part sequencing problem in a robotic cell with three machines, for different periodical patterns of robot moves, when the objective is productivity maximization.

Scheduling of flexible flow lines in an automobile assembly plant

This paper deals with the material flow management in a large-scale manufacturing process, namely the assembly of automobiles in a highly automated plant in Italy. After a detailed description of the plant from the viewpoint of material flow issues, the modeling process and the methodologies employed to address the problems are illustrated. The decision models were validated by means of simulations of the real plant in several different production scenarios (varying demand volume and mix, resource availability etc.).

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.

The Inspection Station Location Problem In Hazardous Material Transportation: Some Heuristics And Bounds

AbstractTo enforce rules regarding hazardous material transportation, regulating agencies need to make choices on where to inspect trucks on the underlying transportation network. If each inspectio...

Coordination of production and interstage batch delivery with outsourced distribution

In this paper, we consider coordinated production and interstage batch delivery scheduling problems, where a third-party logistics provider (3PP) delivers semi-finished products in batches from one production location to another production location belonging to the same manufacturer. A batch cannot be delivered until all jobs of the batch are completed at the upstream stage. The 3PP is required to deliver each product within a time T from its release at the upstream stage. We consider two transportation modes: regular transportation, for which delivery departure times are fixed at the beginning, and express transportation, for which delivery departure times are flexible. We analyze the problems faced by the 3PP when either the manufacturer dominates or the 3PP dominates. In this context, we investigate the complexity of several problems, providing polynomiality and NP-completeness results.

A job-shop problem with one additional resource type

We consider a job-shop scheduling problem with n jobs and the constraint that at most p<n jobs can be processed simultaneously. This model arises in several manufacturing processes, where each operation has to be assisted by one human operator and there are p (versatile) operators. The problem is binary NP-hard even with n=3 and p=2. When the number of jobs is fixed, we give a pseudopolynomial dynamic programming algorithm and a fully polynomial time approximation scheme (FPTAS). We also propose an enumeration scheme based on a generalized disjunctive graph, and a dynamic programming-based heuristic algorithm. The results of an extensive computational study for the case with n=3 and p=2 are presented.

Nondominated Schedules for a Job-Shop with Two Competing Users

We consider the scenario where two users compete to perform their respective jobs on a common set of resources. The job for each user has a due-date and the cost function associated with the due-date is quasi-convex (i.e., it has a single local minimum). We characterize the set of nondominated schedules over which the users may negotiate and develop a polynomial algorithm to find this nondominated set.