Browsing by Subject "Beam Search"

Now showing 1 - 4 of 4

Open Access
Analysis of reactive scheduling problems in manufacturing systems
(1997) Bayız, Murat
In this study we develop a new scheduling algorithm for the job shop problem. The proposed algorithm is a heuristic method based on the filtered beam search. After extensive analyses on the evaluation functions and search parameters of the beam search, we measure the performance of the algorithm in terms of quality of solutions and CPU times for both the makespan and mean tardiness criteria. In the second half of the research, we study the reactive scheduling problem. Specifically, we analyze several reactive methods such as no response, periodic response and continuous response under various experimental conditions. The beam search based partial scheduling is also studied in this thesis. The method is analyzed for both deterministic and stochastic environments under several job shop configurations.
Open Access
Balancing straight and U-Type assembly lines with stochastic process times
(2003) Şekerci, Halil
In this thesis, we study the problem of assembly line balancing with stochastic task process times. The research considers both the well-known straight line balancing problem and U-line balancing problem where the line is paced, with no buffer inventories between stations. The objective is to minimize a two component cost function where the cost terms come from cost of manning the line and cost of finishing the incomplete units off the line. Cost is measured by an existing exact method for straight line balancing and a heuristic cost measurement method is developed for U-line balancing. The key idea in the core of this research is a task's marginal desirability for assignment at a given station. This idea is embedded in a beam search heuristic for solving both the straight line and U-line balancing problem. Extensive computational experiments and simulation experiments are made with well-known problems in the literature under the assumption of normally distributed task processing times. The quality of the solutions found by beam search for the straight-line balancing problem is compared to an existing method in literature. A simulation model of the assembly design is constructed and sample results from the U-line balancing problem are tested against the simulation results. The algorithm presented in this thesis improves the objective function by up to 24 percent.
Open Access
Beam search algorithms for the mixed-model assembly line sequencing problem
(2005) Göçgün, Yasin
In this thesis, we study the mixed-model assembly line sequencing problem that considers the following objectives: 1) leveling the part usage, and 2) leveling workload on the final assembly line. We propose Beam Search algorithms for this problem. Unlike the traditional Beam Search, the proposed algorithms have information exchange and backtracking capabilities. The performances of the proposed algorithms are compared with those of the heuristics in the literature. The results indicate that the proposed methods generally outperform the existing heuristics. A comprehensive bibliography is also provided in this study.
Open Access
New solution methods for single machine bicriteria scheduling problem : minimization of average flowtime and number of tardy jobs
(2006) Erenay, Fatih Safa
In this thesis, we consider the bicriteria scheduling problem of minimizing number of tardy jobs and average flowtime on a single machine. This problem, which is known to be NP-hard, is important in practice as the former criterion conveys the customer’s position and the latter reflects the manufacturer’s perspective in the supply chain. We propose two new heuristics to solve this multiobjective scheduling problem. These two heuristics are constructive algorithms which are based on beam search methodology. We compare these proposed algorithms with three existing heuristics in the literature and two new meta-heuristics. Our computational experiments illustrate that proposed heuristics find efficient schedules optimally in most of the cases and perform better than the other heuristics.