Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of ...

Memetic algorithms (MAs) are meta-heuristics that join genetic algorithms with hill climbing. MAs have recognized success in solving difficult search and optimization problems. Hyperheuristics are proposed as an alternative to meta-heuristics. A hyperheuristic is a mechanism that chooses a heuristic from a set of heuristics, applies it to a candidate solution, and then makes a decision for acce...

In this paper we propose some non-greedy heuristics and develop an Augmented-Neural-Network (AugNN) formulation for solving the classical open-shop scheduling problem (OSSP). AugNN is a neural network based meta-heuristic approach that allows integration of domain-specific knowledge. The OSSP is framed as a neural network with multiple layers of jobs and machines. Input, output and activation f...

Combinatorial optimization problems are often used to test heuris-tics. Among heuristics, stochastic ones deserve particular consideration being generally meta-heuristics that aim at performing reasonnably well on a wide spectrum of problems. Among them, evolutionary algorithms have recently appeared. Emphasis have been put on them by researches that have shown that they are able to solve eecie...