Serial Schedule Research Articles

Rate-0.96 LDPC Decoding VLSI for Soft-Decision Error Correction of NAND Flash Memory

The reliability of data stored in high-density Flash memory devices tends to decrease rapidly because of the reduced cell size and multilevel cell technology. Soft-decision error correction algorithms that use multiple-precision sensing for reading memory can solve this problem; however, they require very complex hardware for high-throughput decoding. In this paper, we present a rate-0.96 (68254, 65536) shortened Euclidean geometry low-density parity-check code and its VLSI implementation for high-throughput NAND Flash memory systems. The design employs the normalized a posteriori probability (APP)-based algorithm, serial schedule, and conditional update, which lead to simple functional units, halved decoding iterations, and low-power consumption, respectively. A pipelined-parallel architecture is adopted for high-throughput decoding, and memory-reduction techniques are employed to minimize the chip size. The proposed decoder is implemented in 0.13-μm CMOS technology, and the chip size and energy consumption of the decoder are compared with those of a BCH (Bose-Chaudhuri-Hocquenghem) decoding circuit showing comparable error-correcting performance and throughput.

A particle swarm optimization based hyper-heuristic algorithm for the classic resource constrained project scheduling problem

In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic algorithm for solving the resource constrained project scheduling problem (RCPSP). To the best of our knowledge, this is the first attempt to develop a PSO hyper-heuristic and apply to the classic RCPSP. The hyper-heuristic works as an upper-level algorithm that controls several low-level heuristics which operate to the solution space. The solution representation is based on random keys. Active schedules are constructed by the serial scheduling generation scheme using the priorities of the activities which are modified by the low-level heuristics of the algorithm. Also, the double justification operator, i.e. a forward–backward improvement procedure, is applied to all solutions. The proposed approach was tested on a set of standard problem instances of the well-known library PSPLIB and compared with other approaches from the literature. The promising computational results validate the effectiveness of the proposed approach.

Effective Project Scheduling Under Workspace Congestion and Workflow Disturbance Factors

Effective project management implies the use of advanced planning and scheduling methods that allow to determine feasible sequences of activities and to complete a project on time and on budget. Traditional scheduling tools like fundamental Critical Path Method (CPM) and various methods for Resource Constrained Project Scheduling Problem (RCPSP) and Time Constrained Project Scheduling Problem (TCPSP) have many shortcomings for construction projects where spatial factor plays a critically important role. Previous attempts to interpret space as a specific resource were successful for particular problems of line-of-balance scheduling, space scheduling, dynamic layout planning, horizontal and vertical logic scheduling, workspace congestion mitigating, scheduling multiple projects with movable resources, spatial scheduling of repeated and grouped activities and motion planning. However, none of these methods considers the spatio-temporal requirements in a holistic framework of generic RCPSP problem and provides feasible results accounting for workspace and workflow factors. In this paper we start with the classical RCPSP statement and then present mathematically strong formalisation of the extended generalised problem, taking into account workspace congestion and workflow disturbance constraints specified in practically meaningful and computationally constructive ways. For the generalised RCPSP problem an effective scheduling method is proposed. The method tends to minimise the project makespan while satisfying timing constraints and precedence relations, not exceeding resource utilisation limits, avoiding workspace congestions and keeping workflows continuous. The method reuses so-called serial scheduling scheme and provides for additional computational routines and heuristic priority rules to generate feasible schedules satisfying all the imposed requirements. Advantages of the method and prospects for its application to industrial needs are outlined in the paper too.

Комплексный метод составления расписаний для сложных индустриальных программ с учетом пространственно-временных ограничений

Effective project management implies the use of advanced planning and scheduling methods that allow to determine the feasible sequences of activities and to complete a project on time and on budget. Traditional scheduling tools like fundamental Critical Path Method (CPM) and various methods for Resource Constrained Project Scheduling Problem (RCPSP) and Time Constrained Project Scheduling Problem (TCPSP) have many shortcomings for the construction projects where spatial factor plays critically important role. Previously taken attempts to interpret space as a specific resource were successful for particular problems of line-of-balance scheduling, space scheduling, dynamic layout planning, horizontal and vertical logic scheduling, workspace congestion mitigating, scheduling multiple projects with movable resources, spatial scheduling of repeated and grouped activities, motion planning. However, none of these methods considers the spatio-temporal requirements in a holistic framework of generic RCPSP problem and provides feasible results accounting for workspace and workflow factors. In the paper we start with the classical RCPSP statement and then present mathematically strong formalization of the extended generalized problem taking into account workspace congestion and workflow disturbance constraints specified in practically meaningful and computationally constructive ways. For the generalized RCPSP problem an effective scheduling method is proposed. The method tends to minimize the project makespan while satisfying timing constraints and precedence relations, not exceeding resource utilization limits, avoiding workspace congestion and keeping workflows continuous. The method reuses so-called serial scheduling scheme and provides for additional computational routines and heuristic priority rules to generate feasible schedules satisfying all the imposed requirements. In order to evaluate the method, benchmark sets are proposed and investigated. Advantages of the method and prospects for its application to industrial needs are outlined in the paper too.

The effect of a short bout of practice on reaching behavior in late preterm infants at the onset of reaching: A randomized controlled trial

The purpose of this study was to examine the effects of a short bout of practice on reaching behavior in late preterm infants at the onset of goal-directed reaching. The study was designed as a blind, three-arm parallel-group, randomized controlled, clinical trial. Thirty-six late preterm infants were recruited from a maternity hospital and allocated according to computer generated randomization into groups that received reaching practice based on either a blocked schedule, a serial schedule, or no practice. Practice consisted of a 4 min session of induced reaching using a toy in three activities guided by a physical therapist. The activities were elicited in separate blocks for the blocked practice group and in a pre-established order for the serial practice group. The control group stayed in the physical therapist's lap but was not stimulated to reach. The infants were assessed 3.3±1.4 days after the onset of goal-directed reaching in three tests: pre-test (immediately before practice), post-test (immediately after practice), and retention test (24 h after post-test). During assessments, the infants were seated in a baby chair and a toy was presented at his/her midline within reaching distance for 2 min. Changes in the number of reaches, proportions of uni/bimanual reaches and kinematic parameters of reaching were main outcome measures. From pre- to post-test, the amount of reaches and bimanual reaches increased in the serial practice group, but the increase was not maintained in the retention test. Kinematic parameters were not affected by practice. Changes in the reaching behavior of late preterm infants can be triggered after the first few minutes of toy-oriented experience based on a serial practice schedule. These changes are not consolidated one day later.

Ant colony optimization-based multi-mode scheduling under renewable and nonrenewable resource constraints

Abstract An ant colony optimization (ACO)-based methodology for solving the multi-mode resource-constrained project scheduling problem (MRCPSP) considering both renewable and nonrenewable resources is presented. With regard to the MRCPSP solution consisting of activity sequencing and mode selection, two levels of pheromones are proposed to guide search in the ACO algorithm. Correspondingly, two types of heuristic information and probabilities as well as related calculation algorithms are introduced. Nonrenewable resource-constraint and elitist-rank strategy are taken into account in updating the pheromones. The flowchart of the proposed ACO algorithm is described, where a serial schedule generation scheme is incorporated to transform an ACO solution into a feasible schedule. The parameter-selection and the resultant performance of the proposed ACO methodology are investigated through a series of computational experiments. It is expected to provide an effective alternative methodology for solving the MRCPSP by utilizing the ACO theory.

Solving resource-constrained project scheduling problems: Conceptual validation of FLP formulation and efficient permutation-based ABC computation

In this paper, we propose two alternative approaches, applying the facility layout problem (FLP) concept and integrating the permutation-based artificial bee colony (PABC) algorithm, to effectively tackle the resource-constrained project scheduling problem (RCPSP). In the FLP formulation, the constraints are expressed to design the activities in the space constructed by resource and temporal restrictions, without violating the precedence relationships and overlaps between the activities. For dodging the difficulty of the FLP-based model to treat large-sized instances of NP-hard RCPSP, the permutation representation scheme of the PABC algorithm is in turn introduced utilizing the artificial bee colony (ABC) process to search the best solution for RCPSP. In the procedure, a crossover operator and an insert operator following the update equation of the ABC algorithm are devised to augment the effectiveness of computation, whereas a shift operator subject to the resource utilization ratio value is suggested to diversify the solutions. The makespan is then obtained and improved with the assistance of a serial scheduling scheme and a double justification skill. Subsequently, the computational experiments conducted substantiate the conceptual validity of the proposed facility layout formulation for RCPSP and the comprehensive simulation shows the effectiveness of the PABC algorithm for RCPSP.

An improved particle swarm optimization for the resource-constrained project scheduling problem

In this paper, an improved particle swarm optimization (PSO) algorithm is proposed for the resource-constrained project scheduling problem (RCPSP) which is widely applied in advanced manufacturing, production planning, and project management. The algorithm treats the solutions of RCPSP as particle swarms and employs a double justification skill and a move operator for the particles, in association with rank-priority-based representation, greedy random search, and serial scheduling scheme, to execute the intelligent updating process of the swarms to search for better solutions. The integration combines and overhauls the characteristics of both PSO and RCPSP, resulting in enhanced performance. The computational experiments are subsequently conducted to set the adequate parameters and compare the proposed algorithm with other approaches. The results suggest that the proposed PSO algorithm augments the performance by 9.26, 16.17, and 10.45 % for the J30, J60, and J120 instances against the best lower bound-based PSO currently available, respectively. Moreover, the proposed algorithms demonstrate obvious advantage over other proposals in exploring solutions for large-scale RCPSP problems such as the J60 and J120 instances.

Modified Graph-Based Detection Methods for Two-Dimensional Interference Channels

Two-dimensional (2-D) interference channels with inter-symbol interference (ISI) and inter-track interference (ITI) exist in the magnetic recording systems at high areal density. A number of 2-D detection methods have recently been proposed for the multi-track processing of the 2-D channels. Graph-based detector with the belief propagation algorithm appears as an alternative method, but at a degraded performance and high complexity level. In this work, we propose two methods to modify the graph-based (GB) detector. One applies a serial scheduling to the GB detector, while the other modifies the GB detection by ignoring some connections during one direction of the reliability updates in the factor graph leading to the reduction of short cycles. The simulation results show that the proposed GB detectors give better bit error rate performances than the other GB detectors.

Serial Symbol-Reliability Based Algorithm for Decoding Non-Binary LDPC Codes

A symbol-reliability based decoding algorithm with serial schedule for non-binary low-density parity-check (LDPC) codes is presented. Performance results, together with implementation complexity analysis, are provided for different sample codes. The proposed algorithm achieves a similar gain to the min- max algorithm for codes with column weight dv ≥ 6, with lower complexity than previous symbol-reliability based algorithms.

Factors affecting the development of workforce versatility

Among all strategies supporting the firms' flexibility and agility, the development of human resources versatility holds a promising place. This article presents an investigation of the factors affecting the development of this flexibility lever, related to the problem of planning and scheduling industrial activities, taking into account two dimensions of flexibility: the modulation of working time, which provides the company with fluctuating work capacities, and the versatility of operators: for all the multi-skilled workers, we adopt a dynamic vision of their competences. Therefore, this model takes into account the evolution of their skills over time, depending on how much they were put in practice in previous periods. The model was solved by using an approach relying on genetic algorithm that used an indirect encoding to build the chromosome genotype, and then a serial scheduling scheme is adopted to build the solution.

Parallel Schedule Method of SMP2 Models under SOA

To achieve the parallel schedule of SMP2 models under the Service Oriented Architecture, a parallel schedule method of SMP2 model is put forward. The assignment method of serial model schedule task is promoted based on the analysis of the four traditional serial model schedule tasks in the SMP2.Then three schedule tasks which can not be scheduled parallelized were reformed and the schedule processes were introduced. Finally, the schedule service interface was extended and the parallel simulation component interface, time manager interface and message manager interface were defined to conduct the implementation of parallel simulation component.

A polarized adaptive schedule generation scheme for the resource-constrained project scheduling problem

This paper presents a hybrid schedule generation scheme for solving the resource-constrained project scheduling problem. The scheme, which is called the Polarized Adaptive Scheduling Scheme (PASS), can operate in a spectrum between two poles, namely the parallel and serial schedule generation schemes. A polarizer parameter in the range between zero and one indicates how similarly the PASS behaves like each of its two poles. The presented hybrid is incorporated into a novel genetic algorithm that never degenerates, resulting in an effective self-adaptive procedure. The key point of this genetic algorithm is the embedding of the polarizer parameter as a gene in the genomes used. Through this embedding, the procedure learns via monitoring its own performance and incorporates this knowledge in conducting the search process. The computational experiments indicate that the procedure can produce optimal solutions for a large percentage of benchmark instances. FullText for HTML: https://doi.org/10.1051/ro/2012006

Receiving-peer-driven multi-video-source scheduling algorithms in mobile P2P overlay networks

This paper proposes two algorithms for multi-video-source in a new mobile P2P architecture for streaming media systems. One is serial, and the other is parallel. When the service peer set providing expected QoS is not empty, the former is called, otherwise the latter is called. The former triggers the video source change event, re-selects a video source, and synchronizes the multi-video-source by the time model of the streaming sequence when QoS is degraded. The latter allows the multiple video sources to concurrently send the data to the receiving peer according to the assigned transmission. Compared to the existing papers, the contribution of this paper is fourfold: (1) the serial and parallel scheduling algorithms, correctly switched according to the actual situation, are firstly proposed; (2) the mobile feature of peers are firstly considered and validated; (3) the client nodes have better and smoother video quality; (4) our algorithms have shorter run time, which is a crucial factor for an on-line system.

Serial Belief Propagation for The High-Rate LDPC Decoders and Performances in The Bit Patterned Media Systems With Media Noise

In this work, we propose to use the serial belief propagation or serial scheduling in the 2-D bit patterned media (BPM) system with media noise. The serial scheduling methods are applied to the random LDPC codes and quasi-cyclic LDPC (QC-LDPC) codes of high code rates. Both are constructed from the progress-edge growth (PEG) algorithm. We compare the performance of the LDPC codes using the serial belief propagation and the conventional belief propagation (BP) decoding. The simulation results show that the serial scheduling provides a faster convergence speed and a better bit error rate performance than the conventional BP in an AWGN channel. The serial belief propagation is also shown to offer the performance gains over the BP decoding for the BPM system with various media noise levels.

A hybrid estimation of distribution algorithm for solving the resource-constrained project scheduling problem

In this paper, a hybrid estimation of distribution algorithm (HEDA) is proposed to solve the resource-constrained project scheduling problem (RCPSP). In the HEDA, the individuals are encoded based on the extended active list (EAL) and decoded by serial schedule generation scheme (SGS), and a novel probability model updating mechanism is proposed for well sampling the promising searching region. To further improve the searching quality, a Forward–Backward iteration (FBI) and a permutation based local search method (PBLS) are incorporated into the EDA based search to enhance the exploitation ability. Simulation results based on benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed HEDA.

Ant Colony Optimization for Multimode Resource-Constrained Project Scheduling

AbstractAn ant colony optimization (ACO)-based methodology for solving a multimode resource-constrained project scheduling problem (MRCPSP) with the objective of minimizing project duration is presented. With regards to the need to determine sequence and mode selection of activities for the MRCPSP, two levels of pheromones for each ant are proposed to guide the search course in the ACO algorithm. The corresponding heuristics and probabilities for each type of the pheromone are considered, and their calculation algorithms are presented. The flowchart of the proposed ACO algorithm is described, where a serial schedule generation scheme is adopted to transform an ACO solution into a feasible schedule. The effectiveness and efficiency of the proposed ACO methodology are justified through a series of computational analyses. The study is expected to provide a more effective alternative methodology for solving the MRCPSP by utilizing the ACO theory.

An effective shuffled frog-leaping algorithm for resource-constrained project scheduling problem

In this paper, we propose an effective heuristic based on the framework of the shuffled frog-leaping algorithm (SFLA) for solving the resource-constrained project scheduling problem (RCPSP). We encode the virtual frog as the extended activity list (EAL) and decode it by the SFLA-specific serial schedule generation scheme (SSSGS). The initial population is generated by the regret-based sampling method and the priority rule. Then, virtual frogs are partitioned into several memeplexes, and each memeplex evolves by adopting the effective resource-based crossover (RBCO). To enhance the exploitation ability, a combined local search including permutation-based local search (PBLS) and forward–backward improvement (FBI) is performed in each memeplex. To maintain the diversity of each memeplex, virtual frogs are periodically shuffled and reorganized into new memeplexes. Basing on some theoretical analysis, speed-up evaluation methods are proposed to improve the efficiency of the SFLA, which are also suitable for other heuristics designed for RCPSP. In addition, we make use of a design-of-experiment method to determine the set of suitable parameters for the SFLA. Computational results and comparisons with some typical existing algorithms demonstrate the effectiveness of the proposed SFLA.

Research on Multitask Collaborative Scheduling Problem with Heuristic Strategies

According to problems existed in the current farm machinery scheduling process, a new farm machinery scheduling scheme is adopted in this dissertation. The collaborative scheduling model of farm machinery is established and multitask collaborative scheduling algorithm is designed through analyzing the differences between Vehicle Scheduling Problem and agricultural machinery scheduling in the dissertation. Earliest Start Time First and minimal resource allocated capacity first strategies are used in the farm machinery scheduling. The algorithm is useful for the case of machinery owner with sufficient farm machinery. The experiment proves that the collaborative scheduling algorithm is more effective than the serial scheduling algorithm.

An effective shuffled frog-leaping algorithm for multi-mode resource-constrained project scheduling problem

In this paper, an effective shuffled frog-leaping algorithm (SFLA) is proposed for solving the multi-mode resource-constrained project scheduling problem (MRCPSP). In the SFLA, the virtual frogs are encoded as the extended multi-mode activity list (EMAL) and decoded by the multi-mode serial schedule generation scheme (MSSGS). Initially, the mode assignment lists of the population are generated randomly, and the activity lists of the population are generated by the regret-based sampling method and the latest finish time (LFT) priority rule. Then, virtual frogs are partitioned into several memeplexes that evolve simultaneously by performing the simplified two-point crossover (STPC). To enhance the exploitation ability, the combined local search including the multi-mode permutation based local search (MPBLS) and the multi-mode forward–backward improvement (MFBI) is further performed in each memeplex. To maintain the diversity of each memeplex, virtual frogs are periodically shuffled and reorganized into new memeplexes. Computational results based on the well-known benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed SFLA.