Synchronization Constraints Research Articles

Formation control of mobile robot systems incorporating primal-dual neural network and distributed predictive approach

This paper addresses the formation problem for multiple mobile robots with velocity mismatch and system constraints by a distributed model predictive control (DMPC) strategy and a modified virtual structure method. Firstly, a desired virtual structure is employed to generate a set of reference paths for the formation robots. By including approaching angle and path parameter synchronization constraints into cost function, a Nash-based DMPC strategy is presented, where a velocity integral controller is developed to solve the velocity mismatch. Further, consider state and input constraints, the distributed optimization problem is rewritten as a constrained quadratic programming (QP) problem. A PDNN is used to obtain the optimal control input increments, and the stability of the proposed algorithm is analyzed. Moreover, the dynamic formation control is achieved by a modified virtual structure method, and simulation examples are given to verified the effectiveness of the proposed strategies.

Models and algorithms for the delivery and installation routing problem

This paper proposes a variant of the vehicle routing problem with time windows (VRPTW) in which one disposes of two heterogeneous fleets to serve the customers; the first fleet is in charge of deliveries with the possibility to install products while the second one only performs installations. Customers receive some furniture, electronics and home appliances, and may require an installation service according to the items received. Installation can be performed by the deliverymen or by a dedicated installation fleet which needs to be synchronized with the delivery one. Each worker (delivery or installer) has different skills, and thus different installation times. We first formulate the problem as a mixed-integer linear programming model and solve it through a branch-and-bound algorithm. Moreover, we propose a formulation for a variant of the problem which allows the installation service at a customer to be done by more than one worker. We also design a tailored adaptive large neighborhood search heuristic to quickly find good solutions. Several computational experiments with new instances generated for this problem are used to assess the performance of both methods. We also prove the performance of both methods on the test instances of the related VRP with multiple synchronization constraints and the VRP with time windows and driver-specific times, yielding high-quality solutions in a short time using the heuristic and providing new lower bounds with the exact method.

Toward accurate clock drift modeling in Wireless Sensor Networks simulation

The protocols used in Wireless Sensor Networks are subject to very strict temporal synchronization constraints. Radio Duty Cycle (RDC) protocols in particular are characterized by their very high synchronization accuracy requirements. In these protocols, synchronization errors are primarily caused by the natural clock drift observed in real nodes. The impact of the clock drift on the desynchronization issues can be investigated by the use of low-level node simulators.In this paper, we show the limitation of the COOJA simulator to evaluate the impact of the clock drift. We show that its current mote execution model does not faithfully reproduce the requested clock drift. We identify the root cause of these inaccuracies and present a new algorithm that is able to precisely reproduce any requested clock drifts in simulation. On the basis of our understanding, we build a mathematical model of the clock drift error allowing previous authors to estimate the error caused by clock drift inaccuracies in their studies and its impact on their results.To demonstrate the new algorithm, we consider a well-documented RDC protocol issue where the clock drift would cause periodic communication blackouts. This phenomenon was observed on real nodes, but was previously impossible to reproduce by simulation. Our new algorithm not only allows to reproduce the blackouts but also provides additional insights that help to confirm the initial analysis of the phenomenon. Finally, we use our algorithm to implement dynamic clock drift models to simulate the behavior of a clock drift evolving through time. We illustrate this using our linear model to push a RDC protocol to its limits.

End-effector pose and arm-shape synchronous planning methods of a hyper-redundant manipulator for spacecraft repairing

Compared with traditional industrial robots, a hyper-redundant manipulator (HRM) has better flexibility, especially in obstacle avoidance, narrow restricted space crossing and fault-tolerant control. However, mathematical modeling and trajectory planning methods for how a HRM can safety traverse these narrow-confined spaces are highly challenging. This paper proposes an end-effector pose and arm-shape synchronous planning method for a HRM passing through space narrow parallel slits based on extended Jacobian matrix redundancy decomposition(EJMRD). Firstly, for the limited confined space environment, the concept of end-effector poses and arm-shape synchronization constraint is introduced, and the overall framework of the method is given. Then, the kinematics model of the HRM is deduced, and the Jacobian matrix(JM) of this “hybrid active-passive driven-segmented linkage” structure is simplified. Further, the HRM is segmented by the dynamic segmentation method(DSM). Secondly, the arm-shape constraints of the inner arm segment(IAS) are integrated into the JM, and the extended Jacobian matrix(EJM) is established. In addition, the null-space of the EJM is redundantly decomposed to achieve obstacle avoidance of the outer arm segment(OAS). Finally, the Matlab-ADAMS co-simulation and experimental system is built. The above algorithm is verified by the simulation and experiment.

A new constraint programming model and a linear programming-based adaptive large neighborhood search for the vehicle routing problem with synchronization constraints

We consider a vehicle routing problem which seeks to minimize cost subject to time window and synchronization constraints. In this problem, the fleet of vehicles is categorized into regular and special vehicles. Some customers require both vehicles’ services, whose service start times at the customer are synchronized. Despite its important real-world application, this problem has rarely been studied in the literature. To solve the problem, we propose a Constraint Programming (CP) model and an Adaptive Large Neighborhood Search (ALNS) in which the design of insertion operators is based on solving linear programming (LP) models to check the insertion feasibility. A number of acceleration techniques is also proposed to significantly reduce the computational time. The computational experiments show that our new CP model finds better solutions than an existing CP-based ALNS, when used on small instances with 25 customers and with a much shorter running time. Our LP-based ALNS dominates the CP-based ALNS, in terms of solution quality, when it provides solutions with better objective values, on average, for all instance classes. This demonstrates the advantage of using linear programming instead of constraint programming when dealing with a variant of vehicle routing problems with relatively tight constraints, which is often considered to be more favorable for CP-based methods. We also adapt our algorithm to solve a well-studied variant of the problem, and the obtained results show that the algorithm provides good solutions as state-of-the-art approaches and improves four best known solutions.

Temporal constraints and device management for the Skill VRP: Mathematical model and lower bounding techniques

We study a generalization of the Skill VRP that incorporates time windows aspects, precedence and synchronization constraints. Specifically, we are given a logistic network where nodes correspond to customers, and where each customer requires a set of (partially ordered) operations. A set of technicians is available to perform such operations, and each technician is qualified to execute only a subset of them, depending on his skill. By referring to a specific context such as Health Care, customers are patients while technicians are caregivers. In a Field Service context, instead, customers are usually referred to as clients while technicians as field technicians. The innovative aspect is that some operations may require a special device, which must be transported at the customer site and must be present at the customer location together with a technician qualified to use it. Given technician dependent traveling costs, we address the problem of defining the tours for the technicians and for the special device, while respecting the skill compatibility between customers and technicians, and the time windows, precedence and synchronization constraints.We propose a Mixed Integer Linear Programming (MILP) model for the generalized Skill VRP, and present some lower bounding techniques based on the proposed formulation. Preliminary computational experiments show that some lower bounding techniques may rapidly produce good lower bounds, thanks to quite effective valid inequalities. The returned percentage optimality gaps, estimated also thanks to a simple matheuristic, are in fact quite small for several scenarios of medium to large size, by encouraging the use of the proposed lower bounding techniques both as building blocks for designing exact approaches, and also as valuable tools to evaluate the efficacy of more sophisticated heuristic approaches to the problem.

Direct numerical simulations of turbulent flows using high-order asynchrony-tolerant schemes: Accuracy and performance

Direct numerical simulations (DNS) are an indispensable tool for understanding the fundamental physics of turbulent flows. Because of their steep increase in computational cost with Reynolds number (Rλ), well-resolved DNS are realizable only on massively parallel supercomputers, even at moderate Rλ. However, at extreme scales, the communications and synchronizations between processing elements (PEs) involved in current approaches become exceedingly expensive and are expected to be a major bottleneck to scalability. In order to overcome this challenge, we developed algorithms using the so-called Asynchrony-Tolerant (AT) schemes that relax communication and synchronization constraints at a mathematical level, to perform DNS of decaying and solenoidally forced compressible turbulence. Asynchrony is introduced using two approaches, one that avoids synchronizations and the other that avoids communications. These result in periodic and random delays, respectively, at PE boundaries. We show that both asynchronous algorithms accurately resolve the large-scale and small-scale motions of turbulence, including instantaneous and intermittent fields. We also show that in asynchronous simulations the communication time is a relatively smaller fraction of the total computation time, especially at large processor count, compared to standard synchronous simulations. As a consequence, we observe improved parallel scalability up to 262144 processors for both asynchronous algorithms.

Branch-and-price-and-cut for the synchronized vehicle routing problem with split delivery, proportional service time and multiple time windows

This study addresses a vehicle routing problem (VRP) in which demands are discrete, split delivery is allowed, service time is proportional to the units of delivered products, multiple time windows are provided and the demand of each customer must be delivered in only one time window (this requirement is termed synchronization constraint). We formulate this problem into a three-index vehicle-flow model and a set-covering model. Then, we propose a branch-and-price-and-cut algorithm to solve the problem. We compare our branch-and-price-and-cut algorithm with CPLEX based on 252 randomly generated instances and the computational results demonstrate the effectiveness of our algorithm.

Two-echelon vehicle routing problem with time windows and mobile satellites

To tackle the logistics challenges faced by enterprises using unmanned aerial vehicles (UAV) with human-driven vans for parcel deliveries, we introduce the two-echelon vehicle routing problem with time windows and mobile satellites (2E-VRP-TM), which, when solved, optimizes delivery routes for a fleet of van-UAV combinations. Typically, one van carries several UAVs. The first echelon involves time-window-driven parcel deliveries using vans from a distribution center (DC) to customers. The second echelon involves UAVs being dispatched from mobile-satellite vans to serve customers with time windows and directly delivering parcels from the DC. When the first-echelon vehicles park at customer locations and wait for second-echelon vehicle departures and returns, the first-echelon vehicles are used as mobile satellites. We develop a vehicle-flow formulation, in which the mobile-satellite synchronization constraints are included to ensure the echelon interaction. We provide an adaptive large neighborhood search heuristic. Computational experiments evaluate the validity of the 2E-VRP-TM formulation and the effectiveness of the heuristic.

A solution approach to the orienteering problem with time windows and synchronisation constraints

The orienteering problem with time windows and synchronisation constraints, known as the Cooperative Orienteering Problem with Time Windows (COPTW), is a class of problems with some important applications such as in home health care and emergency logistics management, and yet has received relatively little attention. In the COPTW, a certain number of team members are required to collect the associated reward from each node simultaneously and cooperatively. This requirement to have one or more team members simultaneously available at a vertex to collect the reward poses a challenging task. It means that while multiple paths need to be determined as in the team orienteering problem with time-windows (TOPTW), there is the additional requirement that certain paths must meet at some of the vertices. Exact methods are too slow for operational purposes and they are not able to handle large scale instances of the COPTW. In this paper, we address the problem of finding solutions to the COPTW in times that make the approach suitable for use in certain emergency response situations. This is achieved by developing new merit-based heuristics as elements of an Adaptive Large Neighbourhood Search (ALNS) algorithm. We validate the performance of this new approach through an extensive computational study. The computational results show that the proposed method is effective in obtaining high quality solutions in times that are suitable for operational purposes.

On the impact of the synchronization constraint and interconnections in quantum-dot cellular automata

Quantum-dot Cellular Automata (QCA) is an emerging nanotechnology with remarkable performance and energy efficiency. Computation and information transfer in QCA are based on field forces rather than electric currents. As a consequence, new strategies are required for design automation approaches in order to cope with the arising challenges. One of these challenges is the transport of information, which is affected by two particularities of the QCA technology. First, information flow in QCA is controlled by external clocks, and second, QCA is a planar technology in which gates, as well as interconnections, are mostly located in the same layer. The former demands proper synchronization already during the circuit design phase, while the latter results in high area costs for interconnections. This work focuses on both constraints and discusses its impact on the implementation of QCA circuits. Further, the concept of local and global synchronicity in QCA circuits is explored. The obtained results indicate that relaxing the global synchronicity constraint can reduce design size by about 70% while the throughput performance declines by similar values. Additionally, it can be shown that the impact of interconnections in QCA, like wires, fan-outs, and crossovers, is indeed substantial. That means, up to 75% of the total area is occupied by interconnections.

Optimization-Based Distributed Flocking Control for Multiple Rigid Bodies

This letter considers distributed flocking control on the Special Euclidean group for networked rigid bodies. The method captures the three flocking rules proposed by Reynolds: cohesion; alignment; and separation. The proposed controller is based only on relative pose (position and attitude) information with respect to neighboring rigid bodies so that it can be implemented in a fully distributed manner using only local sensors. The flocking algorithm is moreover based on pose synchronization methods for the cohesion/alignment rules and achieves safe separation distances through the application of control barrier functions. The control input for each rigid body is chosen by solving a distributed optimization problem with constraints for pose synchronization and collision avoidance. Here, the inherent conflict between cohesion and separation is explicitly handled by relaxing the position synchronization constraint. The effectiveness of the proposed flocking algorithm is demonstrated via simulation and hardware experiments.

Optimization of a multi-constraint two-sided assembly line balancing problem using an improved imperialist competitive algorithm

PurposeAssembly is the last step in manufacturing processes. The two-sided assembly line balancing problem (TALBP) is a typical research focus in the field of combinatorial optimization. This paper aims to study a multi-constraint TALBP-I (MC-TALBP-I) that involves positional constraints, zoning constraints and synchronism constraints to make TALBP more in line with real production. For enhancing quality of assembly solution, an improved imperialist competitive algorithm (ICA) is designed for solving the problem.Design/methodology/approachA mathematical model for minimizing the weighted sum of the number of mated-stations and stations is established. An improved ICA is designed based on a priority value encoding structure for solving MC-TALBP-I.FindingsThe proposed ICA was tested by several benchmarks involving positional constraints, zoning constraints and synchronism constraints. This algorithm was compared with the late acceptance hill-climbing (LAHC) algorithm in several instances. The results demonstrated that the ICA provides much better performance than the LAHC algorithm.Practical implicationsThe best solution obtained by solving MC-TALBP-I is more feasible for determining the real assembly solution than the best solution obtained by solving based TALBP-I only.Originality/valueA novel ICA based on priority value encoding is proposed in this paper. Initial countries are generated by a heuristic method. An imperialist development strategy is designed to improve the qualities of countries. The effectiveness of the ICA is indicated through a set of benchmarks.

Timetabling for Strategic Passenger Railway Planning

In research and practice, public transportation planning is executed in a series of steps, which are often divided into the strategic, the tactical, and the operational planning phase. Timetables are normally designed in the tactical phase, taking into account a given line plan, safety restrictions arising from infrastructural constraints, as well as regularity requirements and bounds on transfer times. In this paper, however, we propose a timetabling approach that is aimed at decision making in the strategic phase of public transportation planning and to determine an outline of a timetable that is good from the passengers’ perspective. Instead of including explicit synchronization constraints between train runs (as most timetabling models do), we include the adaption time (waiting time at the origin station) in the objective function to ensure regular connections between passengers’ origins and destinations. We model the problem as a mixed integer quadratic program and linearise it. Furthermore we propose a heuristic to generate starting solutions. We illustrate the type of solutions found by our approach on two case studies based on the Dutch railway network and analyse trade-offs that are made to balance dwell times and regularity of trains.

Synchronization Management in Hypermedia Documents

In this paper, we study the problem of synchronization management in hypermedia documents where we proposed a formal approach inspired by separation logic to analyze and correct progressively the temporal, spatial and hypermedia synchronization constraints. For that purpose, we have developed a tool named Hypermedia Document Builder (HDB) to help the authors to design and verify easily all the hypermedia documents constraints’ errors. So, the latter is presented immediately during the design phase to facilitate their correction and to minimize their number. Our HDB tool permits also to adapt the analyzed hypermedia documents to its different standard web presentation formats such as: HTML5 or SMIL 3.0. Finally, the HDB tool has been compared with tools of similar nature of recent related works and the results show that the proposed tool advances the design of such tools.

An Efficient Minimum-Time Cooperative Task Planning Algorithm for Serving Robots and Operators

SUMMARYWe establish an efficient minimum-time cooperative task planning algorithm for robots and operators to serve clients. This problem is an extension of the multiple traveling salesman problem and the vehicle routing problem with synchronization constraints, but it is more difficult due to the cooperative tasks of the robots and operators. To find the exact minimum-time task plan with a small tree size, we propose an efficient branch-and-bound with a good initial tree and keen complementary heuristics. Our algorithm is also effective as an approximate algorithm for the many clients problem within the capacity of the computer used. The efficiency of our algorithm is revealed via case studies: telemedical service robots and planetary exploration robots.

Optimal Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks.

Energy efficiency and end-to-end delay are two of the major requirements for the monitoring and detection applications based on resource-constrained wireless sensor networks (WSNs). As new advanced technologies for accurate monitoring and detection—such as device-free wireless sensing schemes for human activity and gesture recognition—have been developed, time synchronization accuracy becomes an important requirement for those WSN applications too. Message bundling is considered one of the effective methods to reduce the energy consumption for message transmissions in WSNs, but bundling more messages increases the transmission interval of bundled messages and thereby their end-to-end delays; the end-to-end delays need to be maintained within a certain value for time-sensitive applications like factory monitoring and disaster prevention, while the message transmission interval affects time synchronization accuracy when the bundling includes synchronization messages as well. Taking as an example a novel WSN time synchronization scheme recently proposed for energy efficiency, we investigate an optimal approach for message bundling to reduce the number of message transmissions while maintaining the user-defined requirements on end-to-end delay and time synchronization accuracy. Formulating the optimal message bundling problem as integer linear programming, we compute a set of optimal bundling numbers for the sensor nodes to constrain their link-level delays, thereby achieving and maintaining the required end-to-end delay and synchronization accuracy. Extensive experimental results based on a real WSN testbed using TelosB sensor nodes demonstrate that the proposed optimal bundling could reduce the number of message transmissions about 70% while simultaneously maintaining the required end-to-end delay and time synchronization accuracy.

Adaptive large neighborhood search for the vehicle routing problem with synchronization constraints at the delivery location

AbstractA vehicle routing problem with synchronization constraints arises in urban freight transportation, in which context customers require deliveries from one or more logistics service providers. These deliveries should be efficient to reduce idle times at the delivery locations. Idle time is defined as nonservice time between the first and the last delivery received by the customer. We propose a strategy which relies on self‐imposed time windows, and we compare our approach with an exact determination of a feasible schedule and fixed time windows. The results show that idle times can be reduced by 54.12%‐79.77%, with an average cost rise of 9.87%. In addition, self‐imposed time windows provide solutions with 15.74%‐21.43% lower costs than feasibility checks for short runtimes and 13.71%‐21.15% lower than fixed time windows.

A constructive framework for the preventive signalling maintenance crew scheduling problem in the Danish railway system

In this article, we consider the problem of planning preventive maintenance of railway signals in Denmark. This case is particularly relevant as the entire railway signalling system is currently being upgraded to the new European Railway Traffic Management System (ERTMS) standard. This upgrade has significant implications for signal maintenance scheduling in the system. We formulate the problem as a multi-depot vehicle routing and scheduling problem with time windows and synchronisation constraints, in a multi-day time schedule. The requirement that some tasks require the simultaneous presence of more than one engineer means that task synchronisation must be considered. A multi-stage constructive framework is proposed, which first distributes maintenance tasks using a clustering formulation. Following this, a Constraint Programming (CP) based approach is used to generate feasible monthly plans for large instances of practical interest. Experimental results indicate that the proposed framework can generate feasible solutions and schedule a monthly plan of up to 1000 tasks for eight crew members, in a reasonable amount of computational time.

On the Control of Fork-Join Networks

Networks in which the processing of jobs occurs both sequentially and in parallel are prevalent in many application domains, such as computer systems, healthcare, manufacturing, and project management. The parallel processing of jobs gives rise to synchronization constraints that can be a main reason for job delay. In comparison with feed-forward queueing networks that have only sequential processing of jobs, the approximation and control of networks that have synchronization constraints is less understood. One well-known modeling framework in which synchronization constraints are prominent is the fork-join processing network. Our objective is to find scheduling rules for fork-join processing networks with multiple job types in which there is first a fork operation, then activities that can be performed in parallel, and then a join operation. The difficulty is that some of the activities that can be performed in parallel require a shared resource. We solve the scheduling problem for that shared server (that is, which type of job to prioritize at any given time) when that server is in heavy traffic and prove an asymptotic optimality result.The e-companion is available at https://doi.org/10.1287/moor.2018.0935 .