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The purpose of this paper is to present a novel and applied method for optimum designing of plate-finned heat exchanger network. Considering the total annual cost as the objective function, a network of plate-finned heat exchanger is designed and optimized.

Accurate evaluation of plate-finned heat exchanger networks depends on different fin types with 10 different geometrical parameters of heat exchangers. In this study, fin numbers are considered as the main decision variables and geometrical parameters of fins are considered as the secondary decision variables. The algorithm applies heat transfer and pressure drop coefficients correction method and differential evolution (DE) algorithm to obtain the optimum results. In this paper, optimization and minimization of the total annual cost of heat exchanger network is considered as the objective function.

In this study, a novel and applied method for optimum designing of plate-finned heat exchanger network is presented. The comprehensive algorithm is applied into a case study and the results are obtained for both counter-flow and cross-flow plate-finned heat exchangers. The total annual cost and total area of the network with counter-flow heat exchangers were 12.5% and 23.27%, respectively, smaller than the corresponding values of the network with cross-flow heat exchanger.

In this paper, a reliable method is used to design, optimize parameters and the economic optimization of heat exchanger network. Taking into account the importance of plate-finned heat exchangers in industrial applications and the complexity in their geometry, the DE methodology is adopted to obtain an optimal geometric configuration. The total annual cost is chosen as the objective function. Applying this technique to a case study illustrates its capability to accurate design plate-finned heat exchangers to improve the objective function of the heat exchanger network from the economic viewpoint with the design of details.

The purpose of this paper is to characterise the TWIN-RRT* algorithm which solves a motion planning problem in which an agent has multiple possible targets where none of them is compulsory and retrieves feasible, “low cost”, asymptotically optimal and probabilistically complete paths. The TWIN-RRT* algorithm solves path planning problems for both holonomic and non-holonomic robots with or without kinematic constraints in a 2D environment.

It was designed to work equally well with higher degree of freedom agents in different applications. It provides a practical implementation of feasible and fast planning, namely where a closed loop is required. Initial and final configurations are allowed to be exactly the same.

The TWIN-RRT* algorithm computes an efficient path for a single agent towards multiple targets where none of them is mandatory. It inherits the low computational cost, probabilistic completeness and asymptotical optimality from RRT*.

It uses efficiency as cost function, which can be adjusted to the requirements of any given application. TWIN-RRT also shows compliance with kinematic constraints.

The practical application where this work has been used consists of an autonomous mobile robot that picks up golf balls in a driving range. The multiple targets are the golf balls and the optimum path is a requirement to reduce the time and energy to refill as quickly as possible the balls dispensing machine.

The new random sampling algorithm – TWIN-RRT* – is able to generate feasible efficient paths towards multiple targets retrieving closed-loop paths starting and finishing at the same configuration.

The modeling and optimization of a weld bead in the middle of the weld are often simple, as the forming process is dynamically balanced. However, the arc striking (AS) and arc extinguishing (AE) areas of weld beads are generally abnormal because the dynamic processes at these areas are unstable. The purpose of this paper is to investigate the abnormal areas of the weld bead with optimization modeling methods in wire and arc additive manufacturing (WAAM).

A burning-back method was proposed to fill the slanted plane in the AE area. To optimize the welding parameters and obtain the optimal design, a response surface methodology was proposed to build the relationships between the input parameters and response variables.

The proposed burning-back method could fill the slanted plane in the AE area. Second-order models of abnormal areas were developed and the optimization effects were analyzed. The experimental results indicated that the relationship models at both ends were applicable and preferable for the optimization of weld beads.

In this paper, a burning-back method was proposed to optimize the slanted plane in the AE area. Second-order models of abnormal areas were established. The methods and models were preferable in the optimization of the abnormal areas in WAAM.

Simultaneous localization and map building (SLAM), as a state estimation problem, is a prerequisite for solving the problem of autonomous vehicle motion in unknown environments. Existing algorithms are based on laser or visual odometry; however, the lidar sensing range is small, the amount of data features is small, the camera is vulnerable to external conditions and the localization and map building cannot be performed stably and accurately using a single sensor. This paper aims to propose a laser three dimensions tightly coupled map building method that incorporates visual information, and uses laser point cloud information and image information to complement each other to improve the overall performance of the algorithm.

The visual feature points are first matched at the front end of the method, and the mismatched point pairs are removed using the bidirectional random sample consensus (RANSAC) algorithm. The laser point cloud is then used to obtain its depth information, while the two types of feature points are fed into the pose estimation module for a tightly coupled local bundle adjustment solution using a heuristic simulated annealing algorithm. Finally, the visual bag-of-words model is fused in the laser point cloud information to establish a threshold to construct a loopback framework to further reduce the cumulative drift error of the system over time.

Experiments on publicly available data sets show that the proposed method in this paper can match its real trajectory well. For various scenes, the map can be constructed by using the complementary laser and vision sensors, with high accuracy and robustness. At the same time, the method is verified in a real environment using an autonomous walking acquisition platform, and the system loaded with the method can run well for a long time and take into account the environmental adaptability of multiple scenes.

A multi-sensor data tight coupling method is proposed to fuse laser and vision information for optimal solution of the positional attitude. A bidirectional RANSAC algorithm is used for the removal of visual mismatched point pairs. Further, oriented fast and rotated brief feature points are used to build a bag-of-words model and construct a real-time loopback framework to reduce error accumulation. According to the experimental validation results, the accuracy and robustness of the single-sensor SLAM algorithm can be improved.

The light detection and ranging sensor has been widely deployed in the area of simultaneous localization and mapping (SLAM) for its remarkable accuracy, but obvious drift phenomenon and large accumulated error are inevitable when using SLAM. The purpose of this study is to alleviate the accumulated error and drift phenomenon in the process of mapping.

A novel light detection and ranging SLAM system is introduced based on Normal Distributions Transform and dynamic Scan Context with switch. The pose-graph optimization is used as back-end optimization module. The loop closure detection is only operated in the scenario, while the path satisfies conditions of loop-closed.

The proposed algorithm exhibits competitiveness compared with current approaches in terms of the accumulated error and drift distance. Further, supplementary to the place recognition process that is usually performed for loop detection, the authors introduce a novel dynamic constraint that takes into account the change in the direction of the robot throughout the total path trajectory between corresponding frames, which contributes to avoiding potential misidentifications and improving the efficiency.

The proposed system is based on Normal Distributions Transform and dynamic Scan Context with switch. The pose-graph optimization is used as back-end optimization module. The loop closure detection is only operated in the scenario, while the path satisfies condition of loop-closed.

The principle of the medial axis calculation is complicated and difficult to implement. Moreover, the accuracy is not high. Then, as the generated path has an endpoint at the boundary of the polygon, burrs may appear on the surface of the molded piece. This paper aims to improve the warpage deformation of SLM molded parts and the surface quality of molded parts, an improved mid-axis path generation algorithm is proposed.

First, the center point is calculated by the seed point growth method based on the distance transform, and the obtained medial axis has high precision and is suitable for simple polygons and complex polygons. Then, based on the extracted medial axis, a preliminary path is generated, the path is trimmed with MATLAB to remove the redundant path. Finally, a scan along the contour of the polygon is performed to improve the surface quality of the molded part.

The algorithm reduces the internal stress generated during the molding process by continuously changing the scanning direction of the path along the boundary curve of the scanning area, thereby reducing the amount of warpage of the molded part. The result of extraction has a higher precision and wider scope of application than other methods to extract central axis, such as the Voronoi diagram-based method. The path is trimmed to remove redundant paths and the polygon boundaries are scanned to further improve the surface quality of the molded part. The results show that warpage deformation of the proposed algorithm is significantly smaller than the other two methods, thus the forming precision is higher.

An improved medial axis path generation algorithm is proposed in this paper. The proposed method is applied to improve warpage deformation occurring in the SLM process. Seed point growth of distance transformation is used to extracted central axis. The result of extraction has a higher precision and wider scope of application than other methods to extract central axis, such as the Voronoi diagram-based method.

The rapid development of smart cities and green logistics has stimulated a lot of research on reverse logistics, and the diversified data also provide the possibility of innovative research on location-routing problem (LRP) under reverse logistics. The purpose of this paper is to use panel data to assist in the study of multi-cycle and multi-echelon LRP in reverse logistics network (MCME-LRP-RLN), and thus reduce the cost of enterprise facility location.

First, a negative utility objective function is generated based on panel data and incorporated into a multi-cycle and multi-echelon location-routing model integrating reverse logistics. After that, an improved algorithm named particle swarm optimization-multi-objective immune genetic algorithm (PSO-MOIGA) is proposed to solve the model.

There is a paradox between the total cost of the enterprise and the negative social utility, which means that it costs a certain amount of money to reduce the negative social utility. Firms can first design an open-loop logistics system to reduce cost, and at the same time, reduce negative social utility by leasing facilities.

This study provides firms with more flexible location-routing options by dividing them into multiple cycles, so they can choose the right option according to their development goals.

This research is a pioneering study of MCME-LRP-RLN problem and incorporates data analysis techniques into operations research modeling. Later, the PSO algorithm was incorporated into the crossover of MOIGA in order to solve the multi-objective large-scale problems, which improved the convergence speed and performance of the algorithm. Finally, the results of the study provide some valuable management recommendations for logistics planning.

A method for qualitative estimation of reliability of large and complex mechanical and hydraulic systems is presented. It is especially useful for comparison and optimum selection of the structure at the conceptual stage of design when no other information about the salient features or parameters of the system is known. The method permits the identification and analysis of critical paths, loops and subsystems causing failure under different causes and modes. The method is based on graph theory and the graph variants proposed as reliability measures are also modified to yield realistic and useful results. The concept of system graph introduced in the article for dealing with large systems appears to be the most appropriate for analysis, comparison, selection and reliability estimates at the beginning of the system′s design.

Resilience concepts in integrated urban transport refer to the performance of dealing with external shock and the ability to continue to provide transportation services of all modes. A robust transportation resilience is a goal in pursuing transportation sustainability. Under this specified context, while before the perturbations, robustness refers to the degree of the system’s capability of functioning according to its design specifications on integrated modes and routes, redundancy is the degree of duplication of traffic routes and alternative modes to maintain persistency of service in case of perturbations. While after the perturbations, resourcefulness refers to the capacity to identify operational problems in the system, prioritize interventions and mobilize necessary material/ human resources to recover all the routes and modes, rapidity is the speed of complete recovery of all modes and traffic routes in the urban area. These “4R” are the most critical components of urban integrated resilience.

The trends of transportation resilience's connotation, metrics and strategies are summarized from the literature. A framework is introduced on both qualitative characteristics and quantitative metrics of transportation resilience. Using both model-based and mode-free methodologies that measure resilience in attributes, topology and system performance provides a benchmark for evaluating the mechanism of resilience changes during the perturbation. Correspondingly, different pre-perturbation and post-perturbation strategies for enhancing resilience under multi-mode scenarios are reviewed and summarized.

Cyber-physic transportation system (CPS) is a more targeted solution to resilience issues in transportation. A well-designed CPS can be applied to improve transport resilience facing different perturbations. The CPS ensures the independence and integrity of every child element within each functional zone while reacting rapidly.

This paper provides a more comprehensive understanding of transportation resilience in terms of integrated urban transport. The fundamental characteristics and strategies for resilience are summarized and elaborated. As little research has shed light on the resilience concepts in integrated urban transport, the findings from this paper point out the development trend of a resilient transportation system for digital and data-driven management.

Automated guide vehicles (AGVs) are driverless vehicles that perform material handling operations in both flexible and conventional facilities. We provide here a review of recent work on the design of AGV guide paths and dispatching rules, including related issues such as idle vehicle location, and location of pickup and delivery stations. Different types of guide paths and related layouts, including optimal and heuristic approaches to the path design, are reviewed here. Dispatching rules and algorithms, including zone control, are also proposed and compared with commonly‐used rules.