Minimizing total tardiness on one machine is NP-hard
Mathematics of Operations Research
A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
Two-phases Method and Branch and Bound Procedures to Solve the Bi–objective Knapsack Problem
Journal of Global Optimization
Improved genetic algorithm for the permutation flowshop scheduling problem
Computers and Operations Research
Comparison of heuristics for flowtime minimisation in permutation flowshops
Computers and Operations Research
Permutation flowshop scheduling problems with maximal and minimal time lags
Computers and Operations Research
Multicriteria Scheduling: Theory, Models and Algorithms
Multicriteria Scheduling: Theory, Models and Algorithms
Parallel Approaches for Multiobjective Optimization
Multiobjective Optimization
A survey on multi-constrained optimal path computation: Exact and approximate algorithms
Computer Networks: The International Journal of Computer and Telecommunications Networking
Approximating multi-objective scheduling problems
Computers and Operations Research
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In this paper, we propose a new exact method, called the parallel partitioning method (PPM), able to solve efficiently bi-objective problems. This method is based on the splitting of the search space into several areas leading to elementary exact searches. We compare this method with the well-known two-phase method (TPM). Experiments are carried out on a bi-objective permutation flowshop problem (BOFSP). During experiments the proposed PPM is compared with two versions of TPM: the basic TPM and an improved TPM dedicated to scheduling problems. Experiments show the efficiency of the new proposed method.