Sai Hong Tang

An expert fuzzy cognitive map for reactive navigation of mobile robots

A control technique is described for reactive navigation of mobile robots. The problems of large number of rules, and inefficient definition of contributing factors, e.g., robot wheel slippage, are resolved. Causal inference mechanism of the fuzzy cognitive map (FCM) is hired for deriving the required control values from the FCMs motion concepts and their causal interactions. The FCM-based control is proven to be advantageous over rule-based techniques. The developed system is utilized to control a Pioneer platform. The results and comparisons with the related works are given using ActivMedia simulation and a developed FCM simulation tool. An error estimation technique is used to measure the error between the actual and the simulation results.

A genetic algorithm for optimization of integrated scheduling of cranes, vehicles, and storage platforms at automated container terminals

Commonly in container terminals, the containers are stored in yards on top of each other using yard cranes. The split-platform storage/retrieval system (SP-AS/RS) has been invented to store containers more efficiently and to access them more quickly. The integrated scheduling of quay cranes, automated guided vehicles and handling platforms in SP-AS/RS has been formulated and solved using the simulated annealing algorithm in previous literatures. This paper presents a genetic algorithm (GA) to solve this problem more accurately and precisely. The GA includes a new operator to make a random string of tasks observing the precedence relations between the tasks. For evaluating the performance of the GA, 10 small size test cases were solved by using the proposed GA and the results were compared to those from the literature. Results show that the proposed GA is able to find fairly near optimal solutions similar to the existing simulated annealing algorithm. Moreover, it is shown that the proposed GA outperforms the existing algorithm when the number of tasks in the scheduling horizon increases (e.g. 30 to 100).

Distribution Network Design for Fixed Lifetime Perishable Products: A Model and Solution Approach

Nowadays, many distribution networks deal with the distribution and storage of perishable products. However, distribution network design models are largely based on assumptions that do not consider time limitations for the storage of products within the network. This study develops a model for the design of a distribution network that considers the short lifetime of perishable products. The model simultaneously determines the network configuration and inventory control decisions of the network. Moreover, as the lifetime is strictly dependent on the storage conditions, the model develops a trade-off between enhancing storage conditions (higher inventory cost) to obtain a longer lifetime and selecting those storage conditions that lead to shorter lifetimes (less inventory cost). To solve the model, an efficient Lagrangian relaxation heuristic algorithm is developed. The model and algorithm are validated by sensitivity analysis on some key parameters. Results show that the algorithm finds optimal or near optimal solutions even for large-size cases.

The reconfiguration issue of stochastic facility layout design in cellular manufacturing systems

Facility layout is one of the important stages in the design of cellular manufacturing systems. It concerns with the arrangement of facilities within the machine cells and the machine cells in the shop floor in such a way that provides an efficient layout. Globalisation and consequences of its high competition which have challenged the manufacturers by providing uncertain situations in the manufacturing environments, degrades the performance of the manufacturing systems. In this study, the effects of uncertainty in demand of products on the layout of facilities in a cellular manufacturing system have been investigated. For this purpose, a stochastic facility layout model has been proposed that minimises the total material handling cost (both inter-cell and intra-cell), and considers that demand has a normal distribution function. The model has been made more practical by considering the transfer batch size of products and operation sequence of parts. To validate the model, several cases have been demonstrated, and solved by two methods; an optimisation software named Lingo 12.0, and an enumeration method which has been developed in C/C++. The results show that fluctuation in demand scenario (service level) can lead to change in the layout of facilities. In other words, the results show the sensitivity of layout problems in cellular manufacturing systems to variation in demand.

An agile FCM for real-time modeling of dynamic and real-life systems

Fuzzy cognitive map (FCM) is a well-established model of control and decision making based on neural network and fuzzy logic methodologies. It also serves as a powerful systematic way for analyzing real-life problems where tens of known, partially known, and even unknown factors contribute to complexity of a system. FCM-based inference requires a neural activation function much like other neural network systems. In modeling, in addition to an activation function, FCM involves with weight training to learn about relationships as they exist among contributing factors. Therefore, numerous contributing factors could be analyzed to understand the behaviors of factors within a real-life system and to represent it in form of tangible matrices of weights. This article discusses a new incremental FCM activation function, named cumulative activation, and introduces a new weight training technique using simulated annealing (SA) known as agile FCM. Smooth variation of FCM nodes that is due to cumulative nature of inference results into faster convergence, while a unique minimum cost solution is guaranteed using the SA training module that is entirely expert-independent. A combination of these two techniques suits time-related applications where inclusion of temporal features is necessary. The resulted system is examined through numerical example datasets where the candidate FCM shows sensitivity to dynamic variables over time. A real-life example case is included as well to further support the effectiveness of the developed FCM in modeling of natural and complex systems.

Effects of Integration on the Cost Reduction in Distribution Network Design for Perishable Products

Perishable products, which include medical and pharmaceutical items as well as food products, are quite common in commerce and industries. Developing efficient network designs for storage and distribution of perishable products plays a prominent role in the cost and quality of these products. This paper aims to investigate and analyze the impact of applying an integrated approach for network design of perishable products. For this purpose, the problem has been formulated as a mixed integer nonlinear mathematical model that integrates inventory control and facility location decisions. To solve the integrated model, a memetic algorithm (MA) is developed in this study. For verification of the proposed algorithm, its results are compared with the results of an adapted Lagrangian relaxation heuristic algorithm from the literature. Moreover, sensitivity analysis of the main parameters of the model is conducted to compare the results of the integrated approach with a decoupled method. The results show that as the products become more perishable, application of an integrated method becomes more reasonable in comparison with the decoupled one.

Multi Objective Optimization of Coordinated Scheduling of Cranes and Vehicles at Container Terminals

According to previous researches, automated guided vehicles and quay cranes in container terminals have a high potential synergy. In this paper, a mixed integer programming model is formulated to optimize the coordinated scheduling of cranes and vehicles in container terminals. Objectives of the model are to minimize total traveling time of the vehicles and delays in tasks of cranes. A genetic algorithm is developed to solve the problem in reasonable computational time. The most appropriate control parameters for the proposed genetic algorithm are investigated in a medium size numerical test case. It is shown that balanced crossover and mutation rates have the best performance in finding a near optimal solution for the problem. Then, ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the genetic algorithm since it can find near optimal solutions, precisely and accurately.

Effect of length on crashworthiness parameters and failure modes of steel and hybrid tube made by steel and GFRP under low velocity impact

The use of tubes as energy absorption structures has been prevalent for many decades and numerous studies have been done on metal and composite tubes of varying thickness, length and section geometry. This paper extends the work to hybrid tubes and presents the results of experimental work pertaining to the collapse modes and crashworthiness characteristics of hybrid tubes that were subjected to quasi-static axial compressive loading. The hybrid specimens were featured by inner mild steel tube wrapped by a material combination of glass fibres in the form of reinforcing direct roving fabric in thermosetting polyester resin. Tubes were cut at different lengths of the same circular cross-section that encompassed both classical progressive buckling and the global bending modes of failure. Particular attention was paid to the investigate effect of tube length on crashworthiness parameters and critical length to avoid global bending during quasi-static crushing of thin-walled tubes. At first, similar work was done on steel tubes to compare results obtained by hybrid tubes with plain counterparts.

AN ALTERNATIVE APPROACH TO FCM ACTIVATION FOR MODELING DYNAMIC SYSTEMS

Recurrent neural models such as fuzzy cognitive maps (FCM) are well established in decision modeling through progressive variations of systems’ concepts. However, existing activation functions have shortcomings, such as a lack of sensitivity to weights of initial concepts, which is due to exaggerated focus on the training of networks’ causal links. Therefore, in most cases, decision outputs converge toward lower and higher extremes and do not represent gray scales. Another disadvantage is that current models require sufficient time delay for convergence toward results. This makes FCM unable to handle transient changes in input. A new technique has been examined in this article using a real-life example to improve FCM activation in terms of fast response to dynamic stimuli. A simple expert model of hexapod locomotion is developed without focus on weight training. The systems response to stimuli is evaluated through a complete six-phase stride to validate the effectiveness of the developed activation function.

Design of a facility layout model in hybrid cellular manufacturing systems under variable demand

Changes in demand, as one of the issues of volatile manufacturing systems, decline the performance of manufacturing systems over the time; especially, it degrades the effectiveness of layout in manufacturing systems. Although the layout of the arrangement of facilities on the shop floor play a significant role in the effectiveness of manufacturing systems, it has not absorbed the attention of researchers in hybrid manufacturing systems. In this paper, a new mathematical model for facility layout in a hybrid cellular manufacturing system has been proposed, which considers demand varying over the planning horizon. The model minimises the material handling cost. To solve the model, a simulated annealing algorithm from literature has been improved. The comparison of results between two algorithms shows the superiority of the improved algorithm in both the quality of solutions and computational time.