Buffer Of Limited Capacity Research Articles

Job Shop Scheduling with Limited-Capacity Buffers using Constraint Programming and Genetic Algorithms

This article aims to propose a new approach for solving production planning and scheduling in the process industries, in such a way to be adaptable to any manufacturing plant and exploring the use of innovative AI-style technologies. The main contributions of the work are: (i) the design of a specific data format to describe any manufacturing plant (including resources, layout and production recipes), being the input of the method; and (ii) the consideration of limited-capacity production lines with intermediate and final buffers in the optimization. The method involves two stages: the first one corresponds to a deterministic optimization algorithm based on Constraint Programming modelling to solve the JSSP in an ideal scenario with no storage limitation; while the second one is a Genetic Algorithm that only comes into play when the solutions obtained from the first one are infeasible for the available storage, so it is a complementary layer to try to solve the mismatches stochastically.

Algorithms for rescheduling jobs with a LIFO buffer to minimize the weighted number of late jobs

Rescheduling can help to improve the quality of a schedule with respect to an initially given sequence. In this paper, we consider the possibility of rescheduling jobs arriving for processing at a single machine under the following limitations: (a) jobs can only be moved toward the end of the schedule and not toward the front, and (b) when a job is taken out of the sequence, it is put on a buffer of limited capacity before being reinserted in its new position closer to the end of the sequence. The buffer is organized as a stack with a last-in/first-out policy. As an objective function, we consider the minimization of the weighted number of late jobs. For this NP-hard problem, we first provide two different integer linear programming (ILP) formulations. Furthermore, we develop a branch-and-bound algorithm with a branching rule based on the movement of jobs. Then a new pseudo-polynomial dynamic programming algorithm is presented which utilizes dominance criteria and an efficient handling of states. Our computational experiments with up to 100 jobs show that this algorithm performs remarkably well and can be seen as the current method of choice.

Greedy algorithm for local heating problem

This paper studies a planning problem for heating water. Hereby, boilers (e.g. gas or electric boilers, heat pumps or microCHPs) are used to heat the water and store it for domestic demands. We consider a simple boiler which is either turned on or turned off and has a buffer of limited capacity. The energy needed to run the boiler has to be bought on a day-ahead market, so we are interested in a planning which minimizes the cost to supply the boiler with energy. We present a greedy algorithm whose time complexity is O(Tα(T)) where T is the number of time intervals and α is the inverse of Ackermann function.

Online repetitive transcranial magnetic stimulation during working memory in younger and older adults: A randomized within-subject comparison.

Working memory is the ability to perform mental operations on information that is stored in a flexible, limited capacity buffer. The ability to manipulate information in working memory is central to many aspects of human cognition, but also declines with healthy aging. Given the profound importance of such working memory manipulation abilities, there is a concerted effort towards developing approaches to improve them. The current study tested the capacity to enhance working memory manipulation with online repetitive transcranial magnetic stimulation in healthy young and older adults. Online high frequency (5Hz) repetitive transcranial magnetic stimulation was applied over the left dorsolateral prefrontal cortex to test the hypothesis that active repetitive transcranial magnetic stimulation would lead to significant improvements in memory recall accuracy compared to sham stimulation, and that these effects would be most pronounced in working memory manipulation conditions with the highest cognitive demand in both young and older adults. Repetitive transcranial magnetic stimulation was applied while participants were performing a delayed response alphabetization task with three individually-titrated levels of difficulty. The left dorsolateral prefrontal cortex was identified by combining electric field modeling to individualized functional magnetic resonance imaging activation maps and was targeted during the experiment using stereotactic neuronavigation with real-time robotic guidance, allowing optimal coil placement during the stimulation. As no accuracy differences were found between young and older adults, the results from both groups were collapsed. Subsequent analyses revealed that active stimulation significantly increased accuracy relative to sham stimulation, but only for the hardest condition. These results point towards further investigation of repetitive transcranial magnetic stimulation for memory enhancement focusing on high difficulty conditions as those most likely to exhibit benefits.

Skill acquisition as a function of age, hand and task difficulty: Interactions between cognition and action.

Some activities can be meaningfully dichotomised as ‘cognitive’ or ‘sensorimotor’ in nature—but many cannot. This has radical implications for understanding activity limitation in disability. For example, older adults take longer to learn the serial order of a complex sequence but also exhibit slower, more variable and inaccurate motor performance. So is their impaired skill acquisition a cognitive or motor deficit? We modelled sequence learning as a process involving a limited capacity buffer (working memory), where reduced performance restricts the number of elements that can be stored. To test this model, we examined the relationship between motor performance and sequence learning. Experiment 1 established that older adults were worse at learning the serial order of a complex sequence. Experiment 2 found that participants showed impaired sequence learning when the non-preferred hand was used. Experiment 3 confirmed that serial order learning is impaired when motor demands increase (as the model predicted). These results can be captured by reinforcement learning frameworks which suggest sequence learning will be constrained both by an individual’s sensorimotor ability and cognitive capacity.

Environment-Aware Production Schedulingfor Paint Shops in Automobile Manufacturing: A Multi-Objective Optimization Approach.

The traditional way of scheduling production processes often focuses on profit-driven goals (such as cycle time or material cost) while tending to overlook the negative impacts of manufacturing activities on the environment in the form of carbon emissions and other undesirable by-products. To bridge the gap, this paper investigates an environment-aware production scheduling problem that arises from a typical paint shop in the automobile manufacturing industry. In the studied problem, an objective function is defined to minimize the emission of chemical pollutants caused by the cleaning of painting devices which must be performed each time before a color change occurs. Meanwhile, minimization of due date violations in the downstream assembly shop is also considered because the two shops are interrelated and connected by a limited-capacity buffer. First, we have developed a mixed-integer programming formulation to describe this bi-objective optimization problem. Then, to solve problems of practical size, we have proposed a novel multi-objective particle swarm optimization (MOPSO) algorithm characterized by problem-specific improvement strategies. A branch-and-bound algorithm is designed for accurately assessing the most promising solutions. Finally, extensive computational experiments have shown that the proposed MOPSO is able to match the solution quality of an exact solver on small instances and outperform two state-of-the-art multi-objective optimizers in literature on large instances with up to 200 cars.

Dynamic power allocation for a multiuser transmitter with hybrid energy sources

In this paper, we investigate the problem of dynamic power allocation for a multiuser transmitter supplied by hybrid energy sources in details. Specifically, we focus on the hybrid energy sources which include both the traditional power grid and various renewable sources whereby there are a few issues in considerations: (1) The energy harvested jointly from various renewable sources is time-varying and possibly unpredictable and is stored in a limited capacity buffer with battery leakage. (2) At the meantime, the data arrives randomly to the transmitter and queues according to the individual receivers to wait to be transmitted. (3) In addition, the wireless channels fluctuate randomly due to fading. Taking into account the time variant and dynamic features of this system, we develop a dynamic power allocation algorithm for the transmitter with the aim of minimizing the average amount of energy consumption from the power grid over an infinite horizon, subject to all data in queues cannot exceed a given deadline of receivers. The research question is formulated as a stochastic optimization problem, then we utilize Lyapunov optimization to exploit an online algorithm with low complexity, and it does not require prior statistical knowledge of the stochastic processes. Performance analysis of the proposed algorithm is carried out in theory, which shows that the proposed algorithm performs arbitrarily close to the optimal objective value; meanwhile, the algorithm ensures that the maximum delay of all data queues cannot exceed a given value. Finally, performance comparison shows that our proposed algorithm provides not only better performance but also less time delay than other two algorithms.

A mathematical model for productivity rate of APSL segmented on sections with buffers of limited capacity

Automated production lines with high productivity are represented the complex and expensive systems based on mechanical, electric and electronic units, while predicting the efficiency of the automated lines is an important analytical task. Calculating the productivity rate of the automated production serial line (APSL) segmented on sections with embedded buffers of limited capacity is a complex and crucial problem for manufacturers. The productivity rate of APSL with balanced technological processes depends on the reliability of mechanism, workstations, transport and other units. Balancing the machining time leads to an increase in the number of workstations and in productivity rate of APSL. It also leads to an increase in the failure rates and hence to deceasing in the productivity rate of the production line. Solution for enhancing productivity is presented in terms of segmenting of APSL into sections with embedded buffers. This paper represents an analytical solution for the productivity rate of APSL segmented on sections with embedded buffers of limited capacity. The mathematical model for the productivity rate of APSL is derived as a function of the technological parameters, the capacity of the buffers and the number of stations and sections with different failure rates and cycle times.

Optima and equilibria for traffic flow on networks with backward propagating queues

This paper studies an optimal decision problem for several groups of drivers on a network of roads. Drivers have different origins and destinations, and different costs, related to their departure and arrival time. On each road the flow is governed by a conservation law, while intersections are modeled using buffers of limited capacity, so that queues can spill backward along roads leading to a crowded intersection. Two main results are proved: (i) the existence of a globally optimal solution, minimizing the sum of the costs to all drivers, and (ii) the existence of a Nash equilibrium solution, where no driver can lower his own cost by changing his departure time or the route taken to reach destination.

한정된 크기의 버퍼가 있는 흐름 공정 일정계획의 스트레치 최소화

In this paper, a hybrid genetic algorithm (HGA) approach is proposed for an n-job, m-machine flow shop scheduling problem with limited capacity buffers with blocking in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. HGA adopts the idea of seed selection and development in order to improve the exploitation and exploration power of genetic algorithms (GAs). Extensive computational experiments have been conducted to compare the performance of HGA with that of GA.

A new genetic algorithm for lot-streaming flow shop scheduling with limited capacity buffers

Lot-streaming is the process of splitting a job (lot) into a number of smaller sublots to allow the overlapping of operations between successive machines in a multi-stage production system. The use...

Productivity and optimization of section-based automated lines of parallel–serial structure with embedded buffers

Automated production lines of a parallel–serial structure are most productive in the manufacturing area. Designers of automated lines segment into sections with several stations place buffers between the series of sections that enable increasing the productivity rate. The failure of one station leads to stoppage of only one section of the automated line, while other sections continue to work and machine parts are stored or consumed from buffers. In real production condition, the capacity of a buffer is limited, and a buffer can compensate only in part stoppages of sections in an automated line. This article represents a new analytical approach for calculating the productivity rate of the section-based automated line of a parallel–serial action with embedded buffers of limited capacity. It enables to solve the problem of structural optimization of the line by the criterion of a maximal productivity rate, which yields the optimal number of serial and parallel stations, and the number of sections.

A note on sorting buffers offline

We consider the offline sorting buffer problem. The input is a sequence of items of different types. All items must be processed one by one by a server. The server is equipped with a random-access buffer of limited capacity which can be used to rearrange items. The problem is to design a scheduling strategy that decides upon the order in which items from the buffer are sent to the server. Each type change incurs unit cost, and thus, the objective is to minimize the total number of type changes for serving the entire sequence. This problem is motivated by various applications in manufacturing processes and computer science, and it has attracted significant attention in the last few years. The main focus has been on online competitive algorithms. Surprisingly little is known on the basic offline problem.In this paper, we show that the sorting buffer problem with uniform cost is NP-hard and, thus, close one of the most fundamental questions for the offline problem. On the positive side, we give an O(1)-approximation algorithm when the scheduler is given a buffer only slightly larger than double the original size. We also sketch a fast dynamic programming algorithm for the special case of buffer size 2.

Processing Lexical Tones and Emotional Tones in Precategorical Acoustic Storage

Precategorical acoustic storage (PAS) is described as a limited capacity buffer store in which acoustic traces are overwritten by successive auditory events. The goal of this study is to extend the function of PAS by investigating whether the recency effect and the suffix effect could also be found when Mandarin lexical tones and emotional tones are recalled in a serial order. Four experiments were conducted. In Experiments 1 and 2, participants were asked to recall lexical tones in a serial order. In these experiments, the recency effect and the suffix effect were found. In Experiments 3 and 4, emotional tones were required to be recalled in a serial order. Both effects were also found. The results of our current study suggest that lexical tones and emotional tones are represented independently in PAS, but their representation status is affected by the attributes of suffix. The results also implied that representations of Mandarin pitch patterns were not as stable as segmental fragments, revealing their special status in short-term memory processing. A serial of lexical tones served as experimental stimuli in Experiments 1 and 2. In Experiment 1, 20 undergraduates were required to give immediate serial recall of the lexical tones presented auditorily via speech. In Experiment 2, a suffix was presented at the end of each serial of lexical tones. Another 20 undergraduates were asked to verbally report the serial as soon as the suffix disappeared. In that lexical tones have a close relationship with vowels, four types of suffixes were prepared at the end of each serial and were further compared with the results of Experiment 1. The results of the two experiments indicated that lexical tones, regardless of suffix type, showed a similar recency effect and suffix effect as vowels in serial recall performance. These findings imply a representation in PAS. A serial of emotional tones served as experimental stimuli in Experiments 3 and 4, which aimed to discover whether emotional tones also show the recency effect and the suffix effect, thus represented in PAS as well. The suffix in Experiment 4 was either consistent or inconsistent with the final item’s emotional information. The results of Experiment 3 indicated that emotional tones reveal a recency effect in the serial recall task. The results of Experiment 4 were compared with those of Experiment 3, and it was found that emotional tones had the suffix effect only when the emotional information of the suffix was inconsistent with that of the final item. The relationship between the suffix and the final item may be a critical factor that causes the suffix effect. Our results are consistent with the notion that PAS, as a sensory memory system, is a storage that can represent and process various aspects of speech information in a similar way. Further implications of our findings are also discussed in terms of specific attributes of lexical tones and emotional tones.

Mathematical formulations for scheduling in manufacturing cells with limited capacity buffers

In the past decade, the deadlock-free scheduling problem in flexible manufacturing systems has received much attention from researchers and practitioners. This is due to the growing trend of automation, and the rising need for flexible manufacturing systems that can cope with the everyday changing market demand. In this article, mixed-integer programming formulations for the deadlock-free scheduling problem of flexible manufacturing cells are proposed. A job shop environment is assumed where each job may have a different processing route. The proposed models consider the presence of different types of buffers in the system. Furthermore, to enhance the comprehensiveness of the models, a heuristic to insert transportation operations into the obtained schedules is proposed. Finally, computational experiments are conducted to investigate the performance of the proposed models in terms of efficiency and computational time.

Deadlock-free scheduling of flexible job shops with limited capacity buffers

In this paper, Mixed Integer Programming (MIP) formulations of the deadlock-free job shop scheduling problem are proposed. The presence of buffer space with limited capacity is considered. This research work also proposes a novel operations insertion algorithm based on the rank matrix (or Latin rectangle). In this algorithm, rank matrices are used to generate the schedules and to check for deadlock situations. Finally, an insertion algorithm is proposed to insert transportation operations in the obtained schedules. Performance evaluations of the proposed mathematical models and the proposed algorithm are conducted. The results show that the mathematical models outperform a model presented earlier in the literature. The results also show that the proposed algorithm obtains the same or better solutions when compared to other solution methodologies reported in the literature. [Submitted 31 July 2007; Revised 14 October 2007; Accepted 14 October 2007]

A lexicographic approach to bi-objective scheduling of single-period orders in make-to-order manufacturing

This paper presents a lexicographic approach and integer programming formulations for a dual-objective, long-term production scheduling in make-to-order manufacturing environment. The problem objective is to assign single-period customer orders for various product types to planning periods to complete all the orders with minimum number of tardy orders as a primary criterion and to level the aggregate production or the total capacity utilization over a planning horizon as a secondary criterion. Each order must be completed during one planning period. The basic integer programming formulation has been strengthened by the addition of some cutting constraints derived by relating the demand on required capacity to available capacity for each subset of orders with the same due date. The approach has been applied to optimize production schedules in a flexible flowshop made up of several processing stages in series, with identical, parallel machines, and an output buffer of limited capacity for holding completed products before delivery to the customers. Numerical examples modeled after a real-world make-to-order flexible assembly line in the electronics industry are provided and some computational results are reported.

Human Memory Systems: A Framework for Understanding Dementia

Human Memory Systems: A Framework for Understanding Dementia

Job-shop scheduling with limited capacity buffers

In this paper we investigate job-shop problems where limited capacity buffers to store jobs in non-processing periods are present. In such a problem setting, after finishing processing on a machine, a job either directly has to be processed on the following machine or it has to be stored in a prespecified buffer. If the buffer is completely occupied the job may wait on its current machine but blocks this machine for other jobs. Besides a general buffer model, also specific configurations are considered. The aim of this paper is to find a compact representation of solutions for the job-shop problem with buffers. In contrast to the classical job-shop problem, where a solution may be given by the sequences of the jobs on the machines, now also the buffers have to be incorporated in the solution representation. In a first part, two such representations are proposed, one which is achieved by adapting the alternative graph model and a second which is based on the disjunctive graph model. In a second part, it is investigated whether the given solution representation can be simplified for specific buffer configurations. For the general buffer configuration it is shown that an incorporation of the buffers in the solution representation is necessary, whereas for specific buffer configurations possible simplifications are presented.

Exact analysis of a discrete material three-station one-buffer merge system with unreliable machines

In this paper, a model of a discrete material flow line consisting of three unreliable machines and one buffer of limited capacity is analysed. A similar system, but with continuous flow of material was examined by Helber and Mehrtens (2001) and Tan (2001). In our system it is assumed that the buffer has two immediate preceding machines, performing the same operations and one immediate succeeding machine that receives material from the buffer. For the case where the buffer reaches its own capacity, one of the two preceding machines has priority over the other to dispose its processed part into the buffer. Processing times are assumed to be deterministic and identical for all machines and are taken as the time unit. Geometrically distributed operation dependent failures at the machines are assumed. All possible transition equations for the examined model are derived and a recursive algorithm that generates the transition matrix for any value N of the storage level is developed. Once the transition matrix is known the performance measures of the model under consideration can be easily evaluated. This model may be used as a building block in a decomposition method to evaluate large production systems with split/merge operations (for example, flow lines with quality inspections and rework loops).