Scheduling Expert System Research Articles

A modular fuzzy expert system for chemotherapy drug dose scheduling

This study presents a modular Fuzzy Expert System (FES) for chemotherapy drug dose scheduling. The computational model considers the patient’s Body Surface Area (BSA) and experts’ opinions to calculate chemo doses following the clinical practice. A proper balance between reducing cancerous cells and toxic side effects is required for effective drug scheduling. Still, in many cases, traditional clinical approaches fail to determine appropriate therapeutical doses that balance all restrictions. In our proposed system, FES-1 is developed to determine primary drug doses based on experts’ opinions and competing treatment objectives. To adjust the dose, FES-2 is developed based on clinical practices, the patient’s BSA, and experts’ opinions. The final chemotherapy drug dose schedule is generated by combining the outputs of FES-1 and FES-2, which is the proposed modular FES. A growth model is used in this work to observe response due to administration of chemotherapy drug doses and to determine the following doses by considering cancer patients’ three weight patterns (increasing, decreasing, and random order). Extensive simulation results and comparative assessment with other current computational chemotherapy drug scheduling models validate the effectiveness and the superiority of the model proposed in this study over the other methods reported in relevant studies.

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

An embedded fuzzy expert system for adaptive WFQ scheduling of IEEE 802.16 networks

WiMAX is a futuristic technology which provides simultaneous support for web, video, and voice applications. WiMAX networks are best suitable to real time traffic however the quantity of non real time and best effort traffic cannot be neglected. Distribution of resources in such heterogeneous applications is therefore a challenging task. There are many schedulers available for WiMAX but adaptive and adequate schedulers are still in growing stage of development. This paper introduces a novel method using which a system is developed based on concepts of fuzzy logic to schedule traffic in WiMAX networks. The proposed fuzzy expert system simplifies fair allocation of resources to real as well as non real time traffic. The implementation is based on changing the weights of the queues serving real and non- real time traffic adaptively. New weights will be calculated for each bandwidth request made to base station and these weights will in turn decide amount of bandwidth allocated to different traffic classes. The weights are calculated based on three parameters that are amount of real time and non real time traffic in queues, change in throughput requirement for non real time flows and latency requirement of real time input data. Results obtained by virtue of simulations justify the significance of the proposed method.

Embedded Technology Parameter Scheduling Optimization Expert System on the Plastic Extruder Applications in Production

In this paper, based on the status quo of plastics extrusion production process at the present stage in China, put forward on the basis of general embedded industrial control scheduling expert system for optimizing the process parameters is established. Structures of the expert system, user interface, the establishment of a knowledge base, reasoning machine design, the learning machine design and so on are introduced. System can according to customer's production goal reasoning out the required process parameter values, and has good portability, instead of the professional engineers for plastics extrusion production process parameters manually, save the human cost, improve the intelligent level of automation and production efficiency.

IRRINET: Large Scale DSS Application for On-farm Irrigation Scheduling

IRRINET is an expert system for irrigation scheduling developed by the CER (Emiliano-Romagnolo Canal Irrigation Consortium), implementing the results of more than 50 years of research on plant/water relation and sustainable irrigation management. The IRRINET project was supported and co-funded by the Emilia-Romagna Region with the aim to progressively reduce water use for irrigation all over the region. IRRINET is among the tools provided to the farmers in the frame of Emilia-Romagna Regional Action Plan for Rural Development 2007-2013. The service started in 1984, on the Videotext network, and, nowadays, IRRINET is spreading in other 6 regions of Italy, with IRRIFRAME project. The following step after the 1984 was in 1999 when IRRINET service was developed on WEB. The IRRINET service is freely available on Internet and provides an ‘irrigation advice’ for the main water demanding crops. The system provides a real-time irrigation scheduling: day-by-day information on how much and when to irrigate farm crops.The aim of present paper is describe the evolution of IRRINET service, the sub-models of IRRINET water balance model and the main development trends. With special attention is analyzed the future development needs in precision irrigation context.

Coordination of maintenance of high-voltage transmission lines and outages of NPP units in an expert maintenance scheduling system

It is shown how a computer-aided maintenance scheduling system can be used to coordinate maintenance of high-voltage transmission lines and outages of NPP units. The paper describes the stages of processing requests for maintenance of power transmission lines, coordination of these requests with the outages of NPP units, and final scheduling followed by plotting of Gantt charts.

Design and Implementation of the Supervisory Control Expert System for Dynamic Scheduling

In the paper, the problem of dynamic scheduling with random disturbance is taken into consideration. Through analyzing the workshop disturbance, the processing strategy and simulation procedure is proposed. On this basis, the supervisory control expert system is developed on the platform of G2. The simulation results given at last illustrate the main function of the system, including manufacturing process monitoring, abnormal event warning, and rescheduling.

Scheduling jobs through multiple parallel channels using an expert system

In recent years, as a result of global competition, the efficiency and effectiveness of business processes are becoming much more critical than ever. Information technology constitutes a critical role as a strategic competitive tool in the global business market. In the previous paradigm, the holistic view was missing and ultimately did not contain real life constraints. The new paradigm is based on the systems approach and represents the real life circumstances of production with applicable and sufficient models. This study is based on an expert system for the scheduling of a manufacturing system. The expert system works with a unique algorithm, which has been developed in this paper. The aim is to develop an expert scheduling system which is realistic and applicable to real life situations. Job specification, machine competence, due date, earliest completion and minimum set up time are the factors which have been taken into account to achieve this aim. As a result, the algorithm achieves both applicability and optimality in solution.

GENESYS: an expert system for production scheduling

Planning and scheduling are forms of decision making, which play a crucial role in manufacturing as well as in service industries. In the current competitive environment, effective sequencing and scheduling has become a necessity for survival in the marketplace. A great challenge for today’s companies is not only how to adapt to this changing, competitive business environment but also how to draw a competitive advantage from the way in which they choose to do so. Intelligent solutions, based on expert systems, to solve problems in the field of production planning and scheduling are becoming more and more widespread nowadays. Proposes an expert system, which uses the prevailing conditions in the industrial environment in order to select and “fire” dynamically the most appropriate scheduling algorithm from a library of many candidate algorithms.

Creating an expert system for detailed scheduling

This paper presents our experience in the development of an expert system to be used for detailed scheduling in an industrial company. This was a middle‐sized company which builds metallic components for the automotive industry. Because of the complexity of the environment where it has to work, with many interactions between related functions in the company, the development of this system has required a great deal of collaboration among different experts. So, we had to develop a more sophisticated methodology for this development. The conclusions extracted from this work lead us to a generalization of the methodology employed, which is also presented here.

Cooperating scheduling systems

An architecture and a procedure for communicating scheduling expert systems based on fuzzy set theory is proposed. Fuzzy sets are used to express and to exchange constraints and their potential relaxation with the cooperating scheduling system that can interpret these constraints. The procedure is intended to optimise global evaluation among the communicating systems. An example from the steel industry is taken to illustrate the approach. Here, a scheduling system of the steel making shop and that of the rolling mill tries to optimise global costs by optimising its own schedules under the observation of the other systems constraints.

Developing a neural network approach for intelligent scheduling in GUESS

The generically used expert scheduling system (GUESS) intelligent scheduling toolkit has been built and applied in various scheduling domains. Previously, GUESS included three major scheduling approaches: a heuristic-based (suggestion tabulator) approach, a hill-climbing algorithm, and a genetic algorithm approach. GUESS has now been expanded to include a neural network scheduling approach. This paper discusses the development, implementation and testing results of the neural network scheduling method within GUESS.

Sufficient search space for spatial expert systems

This paper seeks the sufficient search space for the expert systems locating rectangular and arbitrary-shaped objects placed without rotation within a two-dimensional rectangular space. We found that for the layout of rectangular objects, the convex vertex set of feasible allocation space is a sufficient space to determine a feasible layout. We also found that for the layout of arbitrary-shaped objects, the boundary point set of the feasible allocation space is a sufficient space to determine a feasible layout. These two theorems are proved by developing two respective parallel translation algorithms. These theorems show that the search space can be significantly reduced in finding a feasible layout. Since these theorems were discovered while we were developing a spatial scheduling expert system, we have empirically tested the performance of the reduced search space with real world examples. According to the empirical test for the convex polygonal objects, the vertex set of feasible allocation space is satisfactory enough as a search space although the vertex set is not a sufficient space.

An expert system for maintenance scheduling

An expert system is developed for the efficient scheduling of the maintenance department in an aeronautic engine company. The Proposed Expert Scheduling System (PESS) consists of a database, a knowledge base, an inference mechanism, and an operating mechanism. The database of the PESS can be local and global, and consists of the facts supplied by the users via user interface. During the consultation process, some intermediate conclusions can also be stored into the global database for further decision-making. Evaluation of the PESS is also discussed.

A hierarchical expert system for integrated scheduling of ship berthing, discharging and material transport

Abstract: Berthing ships at a port and unloading the stowed materials require a series of scheduling problems: ship berthing, discharging, and material transport. To deal effectively with the scheduling complexity due to mutual interdependence among those problems, this paper proposes a two‐level hierarchical architecture for the integrated scheduling of all the activities arising in port. The hierarchical architecture assigns ships to multiple lower level dispatchers, each of which makes its own discharging and material transport schedule independently while satisfying the requirements imposed by the higher level coordinator. If any problem occurs within a dispatcher, the higher level coordinator attempts to resolve the trouble through the coordination of other dispatchers. Based on the hierarchical architecture, a prototype scheduling expert system is developed using G2 for the port scheduling problem at a steelworks. Through the object‐ oriented interaction of frames, the system is shown to effectively construct integrated schedules from the berth scheduling to the material transport scheduling.

Modular control system with intelligent scheduling

A modular control system of a flexible manufacturing cell based on microcomputers and local area network is presented. Decentralisation and modularisation as architectural strengths of advanced Shop Floor Control-software (SFC) are emphasised. The system implementation with corresponding control modules is described. An expert routing and scheduling system using rule-based simulation is presented. The use of simulation module tightly connected to the manufacturing process to increase the system throughput is suggested.

A regenerative expert system approach for the maintenance of expert systems

When the maintenance of expert systems incorporates not only knowledge bases but also inference engines, algorithms, and user interface modules, the maintenance of the expert systems needs to adopt software maintenance methodologies such as software reuse. We have developed a regenerative expert system approach (REGENESYS) that can modify the rules and program modules of a standard expert system according to the changed specification. We have also proposed a procedure for the approach and illustrated it with the scheduling expert systems for shipbuilding. By adopting the regenerative expert system approach, we can reduce the burden of developing systems for rare occurrences and maintain the capability of modular modification.

Evaluation of ordering strategies for constraint satisfaction reactive scheduling

Reactive scheduling is essential in any scheduling system to incrementally reconcile the discrepancies between the generative schedule and current status of the factory. Typical events requiring the reactive scheduling process include the delayed delivery of materials, machine breakdown, and failure to meet quality control standards. To efficiently cope with these unexpected events, a reactive scheduling procedure is proposed based on the constraint satisfaction approach, and applied to the reactive adjustment of hot-rolling schedules at steelworks. Various domain-specific strategies are devised as variable and value-ordering heuristics to guide the search directions in the reactive scheduling process, and implemented in a scheduling expert system. From the experiment conducted on the prototype system developed, we find that the schedule performance is mainly determined by the variable ordering strategy based on the criticality of scheduling activities, and it can be further improved by adopting the appropriate value-ordering strategy based on the least constraining resource heuristic.

Expert system for scheduling in an airline gate allocation

Scheduling is an important technique encompassing a wide application area. Because of the complex interrelations among the resources, knowledge, and various other constraints, scheduling has many difficulties. Artificial Intelligence technology has been applied to solve the scheduling problem. As AI techniques are efficient in representing knowledge and dealing with heuristics, it is an adequate approach to model and to solve scheduling problems. We have implemented the ramp scheduling system, called RACES (Ramp Activity Coordination Expert System), to solve complex and dynamic aircraft parking problems. RACES was developed from the domain knowledge and experience which were acquired from the domain experts. Domain knowledge and experience are important factors in controlling the scheduling procedure. RACES divides the problem into sub-problems and experimental heuristics in the knowledge acquisition process. The system independently processes scheduling for the divided sub-problems and shares variables and domains. During the scheduling, the system selects or confines the search space with domain filtering techniques by exploiting the characteristics of various constraints and knowledge. RACES produces a user-driven near-optimal solution by means of a trade-off scheduling method using heuristics between the size of aircraft and the best-fit time. For 400 daily flights, RACES made parking schedules for aircraft in about 20 s compared with 4–5 h by human experts.

A two-level hierarchical approach for raw material scheduling in steelworks

Raw material scheduling problems in steelworks suffer from the computational complexity arising from the interdependence and interference between various items of transport equipment. To deal effectively with such complexity, this paper proposes a two-level hierarchical architecture for the construction of predictive schedules to transport raw materials from stock yards to processing plants. The architecture allocates the raw materials required, to multiple lower-level dispatchers, each of which schedules its reclaimer to withdraw the assigned raw materials. A higher-level scheduler constructs belt-conveyor schedules for transporting the reclaimed raw materials to their processing plants. If any conflict occurs within a dispatcher during the scheduling process, the higher-level scheduler coordinates other dispatchers for conflict resolution. Based on this architecture, a scheduling expert system called RAMS was developed using G2, to automate the raw material scheduling process at a steelworks. By providing the predictive raw material transport schedule, the system is proved to relieve the burden on the human scheduler and to improve schedule performances.