This chapter summarizes some previous work on a constraint-based scheduling approach effectively applied to Resource-Constrained Project Scheduling problems. The approach is based on a formulation of the problem as a Constraint Satisfaction Problem (CSP). In particular the problem is reduced to the one of establishing sufficient precedence constraints between activities that require the same resource so as to eliminate all possible resource contention, defining what is called the Precedence Constraint Posting (PCP) approach. The PCP scheduling approach has two attractive properties: first it operates in a search space that avoids over-commitment to specific activity start times, and can be more efficiently searched; second, the solution generated is a so-called "flexible schedule", designating a set of acceptable futures, which provides a basis for efficiently responding to unexpected disruptions during execution. This chapter summarizes a body of work developed over the years on PCP-based scheduling to take advantage of such properties. In particular, the chapter presents an overview on a number of original algorithms for efficiently finding a solution to a scheduling problem, for generating robust schedules, and for searching near-optimal makespan solutions.
A Precedence Constraint Posting Approach
Cesta Amedeo;Oddi Angelo;
2015
Abstract
This chapter summarizes some previous work on a constraint-based scheduling approach effectively applied to Resource-Constrained Project Scheduling problems. The approach is based on a formulation of the problem as a Constraint Satisfaction Problem (CSP). In particular the problem is reduced to the one of establishing sufficient precedence constraints between activities that require the same resource so as to eliminate all possible resource contention, defining what is called the Precedence Constraint Posting (PCP) approach. The PCP scheduling approach has two attractive properties: first it operates in a search space that avoids over-commitment to specific activity start times, and can be more efficiently searched; second, the solution generated is a so-called "flexible schedule", designating a set of acceptable futures, which provides a basis for efficiently responding to unexpected disruptions during execution. This chapter summarizes a body of work developed over the years on PCP-based scheduling to take advantage of such properties. In particular, the chapter presents an overview on a number of original algorithms for efficiently finding a solution to a scheduling problem, for generating robust schedules, and for searching near-optimal makespan solutions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.