A Flexible flowshop problem with total flowtime minimization

Çakmak, Ergin


A flexible flowshop problem with total flow time minimization
Azizoğlu, Meral; Kondakci, S (Elsevier BV, 2001-08-01)
In this study, we consider total flow time problem in a flexible flowshop environment. We develop a branch and bound algorithm to find the optimal schedule. The efficiency of the algorithm is enhanced by upper and lower bounds and a dominance criterion. Computational experience reveals that the algorithm solves moderate sized problems in reasonable solution times.
A self-organizing neural network approach for the single AGV routing problem
Soylu, M; Özdemirel, Nur Evin; Kayaligil, S (2000-02-15)
In this research, a special form of Automated Guided Vehicle (AGV) routing problem is investigated. The objective is to find the shortest tour for a single, free-ranging AGV that has to carry out multiple pick and deliver (P&D) requests. This problem is an incidence of the asymmetric traveling salesman problem which is known to be NP-complete. An artificial neural network algorithm based on Kohonen's self-organizing feature maps is developed to solve the problem, and several improvements on the basic featur...
A discrete time quasi birth and death model of fixed cycle time policies for stochastic multi-item production inventory problem
Kocabıyıkoğlu, Ayşe; Güllü, Refik; Erkip, Nesim; Department of Industrial Engineering (2000)
A longest path problem for evaluating the worst case packet delay of switched ethernet
Schmidt, Klaus Verner; Schmidt, Şenan Ece (2010-07-09)
In the recent years, the use of real-time Ethernet protocols becomes more and more relevant for time-critical networked industrial applications. In this context, this paper presents a method to compute the worst-case packet delays on switched Ethernet. Based on an evaluation of the packet delays at each switch port and the network topology, we construct a weighted directed graph that allows to find the worst-case end-to-end packet delay by solving a conventional longest-path problem.
A Heuristic temporal difference approach with adaptive grid discretization
Fikir, Ozan Bora; Polat, Faruk; Department of Computer Engineering (2016)
Reinforcement learning (RL), as an area of machine learning, tackle with the problem defined in an environment where an autonomous agent ought to take actions to achieve an ultimate goal. In RL problems, the environment is typically formulated as a Markov decision process. However, in real life problems, the environment is not flawless to be formulated as an MDP, and we need to relax fully observability assumption of MDP. The resulting model is partially observable Markov decision process, which is a more r...
Citation Formats
E. Çakmak, “A Flexible flowshop problem with total flowtime minimization,” Middle East Technical University, 1998.