Using dual approximation algorithms for scheduling problems theoretical and practical results
Journal of the ACM (JACM)
Lower bounds and reduction procedures for the bin packing problem
Discrete Applied Mathematics - Combinatorial Optimization
An integrated model for job-shop planning and scheduling
Management Science
Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
Algorithms for Hybrid MILP/CP Models for a Class of Optimization Problems
INFORMS Journal on Computing
Computers and Operations Research
Manufacturing Planning and Control for Supply Chain Management
Manufacturing Planning and Control for Supply Chain Management
Computers and Operations Research
A hybrid algorithm for a class of resource constrained scheduling problems
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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In this paper we propose a branch-and-cut algorithm for solving an integrated production planning and scheduling problem in a parallel machine environment. The planning problem consists of assigning each job to a week over the planning horizon, whereas in the scheduling problem those jobs assigned to a given week have to be scheduled in a parallel machine environment such that all jobs are finished within the week. We solve this problem in two ways: (1) as a monolithic mathematical program and (2) using a hierarchical decomposition approach in which only the planning decisions are modeled explicitly, and the existence of a feasible schedule for each week is verified by using cutting planes. The two approaches are compared with extensive computational testing.