Browsing by Subject "Beam search"

Now showing 1 - 7 of 7

Open Access
Backtracking and exchange of information: methods to enhance a beam search algorithm for assembly line scheduling
(Elsevier, 2008) Sabuncuoǧlu, İ.; Gocgun, Y.; Erel, E.
Beam search (BS) is used as a heuristic to solve various combinatorial optimization problems, ranging from scheduling to assembly line balancing. In this paper, we develop a backtracking and an exchange-of-information (EOI) procedure to enhance the traditional beam search method. The backtracking enables us to return to previous solution states in the search process with the expectation of obtaining better solutions. The EOI is used to transfer information accumulated in a beam to other beams to yield improved solutions. We developed six different versions of enhanced beam algorithms to solve the mixed-model assembly line scheduling problem. The results of computational experiments indicate that the backtracking and EOI procedures that utilize problem specific information generally improve the solution quality of BS.
Open Access
A beam search algorithm to optimize robustness under random machine breakdowns and processing time variability
(Institute of Industrial Engineers, 2007) Gören, S.; Sabuncuoğlu, İhsan
The vast majority of the machine scheduling research assumes complete information about the scheduling problem and a static environment in which scheduling systems operate. In practice, however, scheduling systems are subject to considerable uncertainty in dynamic environments. The ability to cope with the uncertainty in scheduling process is becoming increasingly important in today's highly dynamic and competitive business environments. In the literature, two approaches have appeared as the effective way: reactive and proactive scheduling. The objective in reactive scheduling is to revise schedules as necessary, while proactive scheduling attempts to incorporate future disruptions when generating schedules. In this paper we take a proactive scheduling approach to solve a machine scheduling problem with two sources of uncertainty: processing time variability and machine breakdowns. We define two robustness measures and develop a heuristic based on beam search methodology to optimize them. The computational results show that the proposed algorithms perform significantly better than a number of heuristics available in the literature.
Open Access
Coordination of inbound and outbound transportation schedules with the production schedule
(Elsevier, 2017) Koç, U.; Toptal, A.; Sabuncuoglu, I.
This paper studies the coordination of production and shipment schedules for a single stage in the supply chain. The production scheduling problem at the facility is modeled as belonging to a single process. Jobs that are located at a distant origin are carried to this facility making use of a finite number of capacitated vehicles. These vehicles, which are initially stationed close to the origin, are also used for the return of the jobs upon completion of their processing. In the paper, a model is developed to find the schedules of the facility and the vehicles jointly, allowing for effective utilization of the vehicles both in the inbound and the outbound. The objective of the proposed model is to minimize the sum of transportation costs and inventory holding costs. Issues related to transportation such as travel times, vehicle capacities, and waiting limits are explicitly accounted for. Inventories of the unprocessed and processed jobs at the facility are penalized. The paper contributes to the literature on supply chain scheduling under transportation considerations by modeling a practically motivated problem, proving that it is strongly NP-Hard, and developing an analytical and a numerical investigation for its solution. In particular, properties of the solution space are explored, lower bounds are developed on the optimal costs of the general and the special cases, and a computationally-efficient heuristic is proposed for solving large-size instances. The qualities of the heuristic and the lower bounds are demonstrated over an extensive numerical analysis.
Open Access
Job shop scheduling with beam search
(Elsevier Science B.V., Amsterdam, Netherlands, 1999) Sabuncuoglu I.; Bayiz, M.
Beam Search is a heuristic method for solving optimization problems. It is an adaptation of the branch and bound method in which only some nodes are evaluated in the search tree. At any level, only the promising nodes are kept for further branching and remaining nodes are pruned off permanently. In this paper, we develop a beam search based scheduling algorithm for the job shop problem. Both the makespan and mean tardiness are used as the performance measures. The proposed algorithm is also compared with other well known search methods and dispatching rules for a wide variety of problems. The results indicate that the beam search technique is a very competitive and promising tool which deserves further research in the scheduling literature.
Open Access
Mixed-model assembly line sequencing using beam search
(Taylor & Francis, 2007) Erel, E.; Gocgun, Y.; Sabuncuoǧlu, İ.
In today's manufacturing environments, companies have to produce a large variety of products in small quantities on a single assembly line. In this paper, we use a beam search (BS) approach to solve the model-sequencing problem of mixed-model assembly lines (MMALs). Specifically, we develop six BS algorithms for part-usage variation and load-leveling performance measures. The results of computational experiments indicate that the proposed BS methods are competitive with the well-known heuristics in the literature. A comprehensive bibliography is also provided.
Open Access
New solution methods for single machine bicriteria scheduling problem: Minimization of average flowtime and number of tardy jobs
(Elsevier, 2010) Erenay, F. S.; Sabuncuoglu, I.; Toptal, A.; Tiwari, M. K.
We consider the bicriteria scheduling problem of minimizing the 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 four new heuristics to solve this multiobjective scheduling problem. Two of these heuristics are constructive algorithms based on beam search methodology. The other two are metaheuristic approaches using a genetic algorithm and tabu-search. Our computational experiments indicate that the proposed beam search heuristics find efficient schedules optimally in most cases and perform better than the existing heuristics in the literature.
Open Access
Stochastic assembly line balancing using beam search
(Taylor & Francis, 2005) Erel, E.; Sabuncuoglu, I.; Sekerci, H.
This paper presents a beam search-based method for the stochastic assembly line balancing problem in U-lines. The proposed method minimizes total expected cost comprised of total labour cost and total expected incompletion cost. A beam search is an approximate branch and bound method that operates on a search tree. Even though beam search has been used in various problem domains, this is the first application to the assembly line balancing problem. The performance of the proposed method is measured on various test problems. The results of the computational experiments indicate that the average performance of the proposed method is better than the best-known heuristic in the literature for the traditional straight-line problem. Since the proposed method is the first heuristic for the stochastic U-type problem with the total expected cost criterion, we only report its results on the benchmark problems. Future research directions and the related bibliography are also provided in the paper.