Pinch-based and disjunctive optimization for process integration of wastewater interception with mass and property constraints

In-plant interception is used to adjust the concentrations and properties of multiple wastewater streams containing pollutants and environmentally-undesirable properties. The determination of the pinch point is critical for the determination of optimum design conditions. Algebraic and graphical techniques are used to locate the pinch point. The selection of the appropriate mass separating agent(s) (MSAs) is based on thermodynamic and economic considerations. A screening procedure is applied to screen competing mass separating agents. Mathematical disjunctive programming is proposed to compare alternatives and invoke the proper models when a certain technology is to be utilized. The model minimizes the total annualized cost, which includes the cost of the selected separating agents and the annualized cost of their associated equipment (depreciation). An example is presented to show the applicability and advantages of the proposed models.     

An agent-based negotiation approach to integrate process planning and scheduling

This paper presents the development of an agent-based negotiation approach to integrate process planning and scheduling (IPPS) in a job shop kind of flexible manufacturing environment. The agent-based system comprises two types of agents, part agents and machine agents, to represent parts and machines respectively. For each part, all feasible manufacturing processes and routings are recorded as alternative process plans. Similarly, alternative machines for an operation are also considered. With regard to the scheduling requirements and the alternative process plans of a part, the proposed agent-based IPPS system aims to specify the process routing and to assign the manufacturing resources effectively. To establish task allocations, the part and machine agents have to engage in bidding. Bids are evaluated in accordance with a currency function which considers an agent's multi-objectives and IPPS parameters. A negotiation protocol is developed for negotiations between the part agents and the machine agents. The protocol is modified from the contract net protocol to cater for the multiple-task and many-to-many negotiations in this paper. An agent-based framework is established to simulate the proposed IPPS approach. Experiments are conducted to evaluate the performance of the proposed system. The performance measures, including makespan and flowtime, are compared with those of a search technique based on a co-evolutionary algorithm.     

A hybrid multi-agent negotiation protocol supporting supplier selection for multiple products with synergy effect

Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.     

Interdependent order allocation in the two-echelon competitive and cooperative supply chain

In this paper, we consider an order allocation problem in a two-echelon supply chain with multiple suppliers and multiple demanders. The orders from the demanders are interdependent in terms of execution sequence. We consider both the competition and cooperation relationships between the suppliers and demanders. We provide formal definition for the order allocation problem and propose a negotiation mechanism which includes a two-stage negotiation protocol and two heuristic negotiation algorithms. Different negotiation strategies are proposed for the demanders and suppliers to resolve the order interdependency and competition conflict. An automated negotiation approach is introduced to implement the negotiation mechanism. The computational experiments show that orders under different supply chain contexts can be allocated with high success rate. We also numerically compare the influence of different negotiation strategies and investigate the interaction of conflict resolutions.     

A multi-agent protocol for multilateral negotiations in supply chain management

Within a supply chain network, it is common for companies to engage in negotiations to resolve conflicts in task allocation and order fulfilment problems. This kind of supply chain negotiation is usually regarded as buyer–seller negotiation. In recent years, multi-agent systems have been established to automate buyer–seller negotiations. However, most have limitations in handling complex negotiation scenarios such as multilateral negotiations and multi-issue negotiations. This paper presents ECNPro (the Extended Contract-Net-like multilateral Protocol), which is a new multi-agent protocol for handling buyer–seller negotiations in supply chain management. ECNPro is designed to handle agent bargaining and interactions in complex multilateral and multi-issue negotiations in which the buyer has to negotiate with many suppliers. The multi-attribute utility theory (MAUT) approach is adopted to establish the utility functions for a set of negotiation issues in the bargaining process. It adopts a multi-threaded approach to allow the buyer to bargain concurrently with multiple suppliers. ECNPro is able to split an order to more than one supplier to achieve a better negotiation payoff. In addition, mobile agents are employed in ECNPro, the buyer sends mobile agents to sites of the sellers to conduct bargaining locally. This approach improves the negotiation efficiency significantly.     

Transactive Demand Response Operation at the Grid Edge using the IEEE 2030.5 Standard

This paper presents a transactive demand response (TDR) scheme for a network of residential customers with generation assets that emphasizes interoperability within a transactive energy architecture. A complete laboratory-based implementation provides the first (to our knowledge) realization of a comprehensive TDR use case that is fully compliant with the Institute of Electrical and Electronics Engineers (IEEE) 2030.5 standard, which addresses interoperability within a cybersecure smart energy profile (SEP) context. Verification is provided by a full system integration with commercial hardware using Internet Protocol (IP)-based (local area network (LAN) and Wi-Fi) communication protocols and transport layer security (TLS) 1.2 cryptographic protocol, and validation is provided by emulation using extensive residential smart meter data. The demand response (DR) scheme is designed to accommodate privacy concerns, allows customers to select their DR compliance level, and provides incentives to maximize their participation. The proposed TDR scheme addresses privacy through the implementation of the SEP 2.0 messaging protocol between a transactive agent (TA) and home energy management system (HEMS) agents. Customer response is handled by a multi-input multi-output (MIMO) fuzzy controller that manages negotiation between the customer agent and the TA. We take a multi-agent system approach to neighborhood coordination, with the TA servicing multiple residences on a common transformer, and use a reward mechanism to maximize customer engagement during the event-based optimization. Based on a set of smart meter data acquired over an extended time period, we engage in multiple TDR scenarios, and demonstrate with a fully-functional IEEE 2030.5-compliant implementation that our scheme can reduce network peak power consumption by 22% under realistic conditions.     

Stub loaded multi-band slotted rectangular microstrip antennas

The multi-band rectangular microstrip antennas (MSAs) realised by placing an open-circuit stub on the edges of the patch and by cutting resonant slots inside the patch are proposed. The multi-port network models for these multi-band rectangular MSAs are also proposed which helps in analysing the voltage distributions at various frequencies. Also the multi-band frequency response of these configurations is experimentally verified.     

Rational Non-Hierarchical Quantum State Sharing Protocol

Rational participants want to maximize their benefits. The protocol with rational participants will be more realistic than the protocol with honest, semi-honest and dishonest participants. We research the rational non-hierarchical quantum state sharing in this paper. General steps of some known quantum state sharing protocol are summarized. Based on these steps, a new rational protocol is proposed. It means that lots of common protocols could be modified to rational protocols. Our protocol is widely applicable. Analyses show that the proposed protocol is rational and secure. It is also all-win for agents. Furthermore, number of deceiving agents is considered to redefine the utilities of agents.     

Conflict detection and resolution for goal formation in the fractal manufacturing system

The fractal manufacturing system (FrMS) is based on the concept of autonomously cooperating agents referred to as fractals. A fractal is a set of self-similar agents whose goal can be achieved through cooperation, coordination, and negotiation among the agents for themselves. A fractal has fractal-specific characteristics (e.g. self-similarity, self-organization, self-optimization, goal-orientation, and dynamics), and it also has the characteristics of an agent (e.g. autonomy, mobility, intelligence, cooperation, and adaptability) at the same time. In the FrMS, a goal can be regarded as the status which the system aspires to be in. The goal-formation process (GFP) in the FrMS is a process of generating goals and modifying them by coordination between agents. In the GFP, conflicts may occur between goals, which can drive a system to become inefficient. In this paper, a conflict resolution mechanism via agent-based negotiation is proposed for facilitating the GFP. The scheme deals with non-fixed goals. The mobile agent-based negotiation process (MANPro), in which a mobile agent is used for information-exchanging and problem-solving, is used for negotiations in this scheme. The proposed mechanism is illustrated with a goal formation scenario in an exemplary FrMS.     

Distributed intelligent control of exceptions in reconfigurable manufacturing systems

In order to react to the continuous and unpredictable changes in product demand, in product variety, and in process technologies, reconfigurable manufacturing systems allow quick adjustment of production capacity and functionality by rearranging or changing their modular components. In this kind of system, operation management issues, such as exception handling policies, become more complex since correct reconfiguration strategies have to be selected. This paper explores the potential of the reconfigurability feature to be a basis for the development of new strategies to handle out-of-the-ordinary events in the production process; in particular, maintaining production flow when machine breakdowns occur. Decisions regarding how to deal with exceptions to the production process are complex and depend on the manufacturing system configuration and on many performance and economic variables. The authors propose agent-based manufacturing control for exception handling because of its ability to be very agile, as well as being reactive and efficient. Manufacturing agents, while working to pursue their specific goals, achieve the global target of the system. Complex decisions can be made due to the synergy arising from the agents' internal reasoning and the negotiation process among these agents. The adopted negotiation mechanism is based on the contract-net protocol, while different strategies have been designed for the internal reasoning. The authors demonstrate that, under certain conditions, an agent's internal strategies based on fuzzy reasoning improve the global performance of the system. The proposed control model has been tested on a discrete event simulation test-bed.     

Bid generation and evaluation for MANPro-based real time scheduling

This paper proposes a bid generation and evaluation scheme and an information model for real-time scheduling. It is well known that an agent-based control approach performs according to both the negotiation mechanism itself and the single agent internal strategic policies. Mobile agent-based negotiation process (MANPro), which has been proposed in our previous work, concerns the first issue of the negotiation mechanism. This paper concerns the second issue of the single agent internal strategic policies. It explains how bids are generated and evaluated and how agents obtain mutual agreement in MANPro. First, the generic bid generation and evaluation framework for MANPro-based negotiation is proposed. Then, the generic framework is applied to a real-time scheduling system for a distributed shop floor control system (SFCS).     

Effectiveness of UK motorway services areas in reducing sleep-related and other collisions

In the UK, motorway service areas (MSAs) are believed to be helpful in reducing sleep (‘fatigue’) related collisions (SRCs), however, their actual effectiveness has yet to be evaluated. During a 2-3-year period, and over two sections of UK motorways comprising 14 MSA sites, assessments were undertaken of all fatal and injury road traffic collisions (RTCs), especially SRCs. Analyses examined whether there was: (i) a reduction in collisions 16 km beyond MSAs compared with the same distance beforehand; (ii) accumulation of collisions with increasing inter-MSA distances. Within the 16 km regions there was a non-significant fall in all RTCs from 355 before MSAs, to 304 afterwards. However, the 22% decrease in SRCs (108 vs. 84) was significant. Cars comprised the greatest reduction in SRCs possibly attributable to a MSA. Including and beyond these 16 km regions, there was no correlation between inter-MSA distances and accumulated RTCs or SRCs (n = 682 of which 181 were SRCs [26%]). There were obvious differences between MSAs in all these respects. Of the 23 fatal RTCs, 17 were SRCs. Whilst SRCs had their greatest daily incidence between 02:00 h and 06:00 h, as expected, MSAs seemed to have their least beneficial effect on SRCs during this vulnerable period, which is a matter for concern.     

A coordination strategy for distributed multi-agent manufacturing systems

This paper proposes a distributed multi-agent approach for dynamic part routing in automated manufacturing systems. In particular, each part in the system is associated to an intelligent software agent that must select its next destination autonomously (i.e. ignoring the actions of the other agents) and in real time (i.e. at each time it completes an operation on a workstation). Differently from other existing approaches, we overcome the typical myopia of negotiation algorithms based on dispatching rules by allowing the part agents to take decisions not only about the imminent operation, but also for the subsequent ones. The anticipated decisions are transmitted to workstation agents, which are also designated to detect and resolve conflicts by modifying part agents’ decisions. To describe the single agents and their interaction schemes in a formal way, we take advantage of DEVS discrete-event modelling tools, which also allow us to develop a detailed simulation platform for our multi-agent system. The simulation experiments obtained on a detailed model of a manufacturing system derived from the literature confirm the effectiveness of the proposed approach.     

A subjective and objective integrated multiple attribute decision making method for material selection

The selection of an optimal material for an engineering design from among two or more alternative materials on the basis of two or more attributes is a multiple attribute decision making (MADM) problem. The selection decisions are complex, as material selection is more challenging today. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel MADM method for material selection for a considered design problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Three examples are presented to illustrate the potential of the proposed method.     

Agent-based manufacturing control based on distributed bid selection and publish-subscribe messaging: a simulation case study

Bidding-based negotiation schemes play a major role in multi-agent manufacturing systems research. Despite some concerns with message congestion, researchers have been proposing and studying negotiation schemes based on the contract net protocol (CNP). On the other hand, research in robotics has considered a variant of CNP based on publish-subscribe messaging designed for multi-robot coordination. A distinct feature of this variant involves distributing the bid evaluation and selection functions among robot agents. This paper discusses our adaptation of this design variant for multi-agent manufacturing systems and examines its performance implications. Using discrete-event simulation, we study how the adapted CNP design can help address the message congestion problem by cutting down on negotiation slack time. Our case study results show that it can enhance the resilience of the agent negotiation process to message congestion, thereby contributing to the overall performance of a multi-agent manufacturing system.     

Feasibility of online collaborative voltage stability control of power systems

The authors present the results of feasibility study of a novel concept of power system online collaborative voltage stability control. Online collaboration between power system controllers is proposed in order to enhance their overall performance and efficiency to cope with the increasing operational uncertainty of modern power systems. The framework of the proposed online collaborative voltage stability control is first presented, which is based on the deployment of multi-agent systems and real-time communication for online collaborative control. Then, two of the most important issues in implementing the proposed online collaborative voltage stability control are addressed: (1) Error-tolerant communication protocol for fast information exchange among multiple intelligent agents; (2) Deployment of multi-agent systems by using graph theory to implement power system post-emergency control. Results of testing the proposed online collaborative voltage stability control in the case of the 10-machine 39-node New England power system are presented. Results of a feasibility study by means of a simulation are given that take into consideration low-probability cascading faults in the power system.     

Flexible job-shop scheduling/rescheduling in dynamic environment: a hybrid MAS/ACO approach

In real-world manufacturing, disruptions are often encountered during the execution of a predetermined schedule, leading to the degradation of its optimality and feasibility. This study presents a hybrid approach for flexible job-shop scheduling/rescheduling problems under dynamic environment. The approach, coined as ‘HMA’ is a combination of multi-agent system (MAS) negotiation and ant colony optimisation (ACO). A fully distributed MAS structure has been constructed to support the solution-finding process by negotiation among the agents. The features of ACO are introduced into the negotiation mechanism in order to improve the performance of the schedule. Experimental studies have been carried out to evaluate the performance of the approach for scheduling and rescheduling under different types of disruptions. Different rescheduling policies are compared and discussed. The results have shown that the proposed approach is a competitive method for flexible job-shop scheduling/rescheduling for both schedule optimality and computation efficiency.     

A comprehensive system for AASHTO PP69-10-based pavement rut evaluation using 1-mm 3D pavement surface model

Measurement of pavement rut is critical to highway agencies for both pavement design and rehabilitation. Historically, rut depth is the only pavement permanent deformation indicator collected with various measurement technologies. Recently, the new draft protocol called AASHTO Standard Practice PP69-10 outlines a set of procedures to derive multiple measures of pavement permanent deformation, including percent deformation, water entrapment depth, rut depth, etc. Multiple parameters can be useful for project-level analysis, but may not be realistic indices for overall permanent deformation evaluation at network level. In this paper, a three-step procedure is applied to evaluate the overall permanent deformation. Transverse profile data are collected on over 200 km (125miles) National Highway Systems using the 1-mm PaveVision3D Ultra data collection system. Twelve attributes for characterising permanent deformation are calculated according to the requirement of PP69-10. Scoring functions of these attributes are elicited using utility theory-based methods with statistics of attributes from the collected sample data-sets. Analytical Hierarchy Process is performed for the development of a comprehensive permanent deformation evaluation system. Additive weights are obtained for all attributes based on pairwise comparisons. A case study is conducted to compare current rut depth-based practice with the proposed new comprehensive evaluation system.     

An integrated approach to the optimization of in-plant wastewater interception with mass and property constraints

This article addresses the problem of in-plant pollution prevention for processes with multiple streams, containing pollutants and environmentally undesirable properties through mass exchange networks (MEN). In-plant interception is used to adjust the concentrations and properties of the wastewater streams. A pinch-based disjunctive-optimization approach is adopted. The determination of the pinch point (being the most constrained thermodynamic and practical operating condition) is critical for determination of optimum design conditions. The selection of the appropriate mass separating agent(s) (MSAs) is based on thermodynamic and economic considerations. A screening procedure modeled through mathematical programming is developed with disjunctive constraints to screen alternatives and invoke the proper models when a certain technology is to be utilized. A case study is solved to illustrate the proposed approach.     

Development and evaluation of the interactive bidding strategies for a demander and its suppliers in supplier selection auction market

Supplier selection strategy is a critical issue in a supply chain management (SCM) system. Selecting the correct suppliers can have a significant impact on the competitiveness of firms. This research is concerned with the development of the interactive bidding strategies for a demander and its multiple suppliers in a supplier selection auction market (SSAM). The objective of this paper is to investigate the negotiation efficiency for the various bidding strategies the demander employed in different order conditions. The negotiation efficiency is assumed as the required negotiation times to achieve an agreement, agreed price and the procurement costs. Further, this paper runs the experiments of SSAM and provides a bidding strategy guideline for a demander to achieve its goals of supplier selection in varying order conditions. To this end, the negotiation efficiency of this proposed bidding strategy model is compared with other research.