A bi-population immune algorithm for weapon transportation support scheduling problem with pickup and delivery on aircraft carrier deck

The weapon transportation support scheduling problem on aircraft carrier deck is the key to restricting the sortie rate and combat capability of carrier-based aircraft.This paper studies the problem and presents a novel solution architecture.Taking the interference of the carrier-based aircraft deck layout on the weapon transportation route and precedence constraint into consideration,a mixed integer formulation is established to minimize the total objective,which is constituted of makespan,load variance and accumulative transfer time of support unit.Solution approach is developed for the model.Firstly,based on modeling the carrier aircraft parked on deck as convex obstacles,the path library of weapon transportation is constructed through visibility graph and Warshall-Floyd methods.We then propose a bi-population immune algorithm in which a population-based forward/backward scheduling technique,local search schemes and a chaotic catastrophe operator are embedded.Besides,the randomkey solution representation and serial scheduling generation scheme are adopted to conveniently obtain a better solution.The Taguchi method is additionally employed to determine key parameters of the algorithm.Finally,on a set of generated realistic instances,we demonstrate that the proposed algorithm outperforms all compared algorithms designed for similar optimization problems and can significantly improve the efficiency,and that the established model and the bi-population immune algorithm can effectively respond to the weapon support requirements of carrier-based aircraft under different sortie missions.

Improved Ant Colony Algorithm for Vehicle Scheduling Problem in Airport Ground Service Support

Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for current operational demands is proposed to study optimization algorithms for vehicle scheduling.The model is based on the constraint relationship of the initial operation time,time window,and gate position distribution,which gives an improvement to the ant colony algorithm(ACO).The impacts of the improved ACO as used for support vehicle optimization are compared and analyzed.The results show that the scheduling scheme of refueling trucks based on the improved ACO can reduce flight delays caused by refueling operations by 56.87%,indicating the improved ACO can improve support vehicle scheduling.Besides,the improved ACO can jump out of local optima,which can balance the working time of refueling trucks.This research optimizes the scheduling scheme of support vehicles under the existing conditions of airports,which has practical significance to fully utilize ground service resources,improve the efficiency of airport ground operations,and effectively reduce flight delays caused by ground service support.

An Architecture of Computer Aided Process Planning System Integrated with Scheduling Using Decision Support System

Process planning and scheduling are two major plann in g and control activities that consume significant part of the lead-time, theref ore all attempts are being made to reduce lead-time by automating them. Compute r Aided Process Planning (CAPP) is a step in this direction. Most of the existin g CAPP systems do not consider scheduling while generating a process plan. Sched uling is done separately after the process plan has been generated and therefore , it is possible that a process plan so generated is either not optimal or feasi ble from scheduling point of view. As process plans are generated without consid eration of job shop status, many problems arise within the manufacturing environ ment. Investigations have shown that 20%～30% of all process plans generated are not valid and have to be altered or suffer production delays when production sta rts. There is thus a major need for integration of scheduling with computer aide d process planning for generating more realistic process plans. In doing so, eff iciency of the manufacturing system as a whole is expected to improve. Decision support system performs many functions such as selection of machine too ls, cutting tools, sequencing of operations, determination of optimum cutting pa rameters and checking availability of machine tool before allocating any operati on to a machine tool. The process of transforming component data, process capabi lity and decision rules into computer readable format is still a major obstacle. This paper proposes architecture of a system, which integrates computer aided p rocess-planning system with scheduling using decision support system. A decisio n support system can be defined as " an interactive system that provides the use rs with easy access to decision models in order to support semi-structured or u nstructured decision making tasks".

Human Machine Collaborative Support Scheduling System of Intelligence Information from Multiple Unmanned Aerial Vehicles Based on Eye Tracker

Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator's attention into consideration.However, the current systems should take advantage of the operator's attention to obtain the optimal solution.In this paper, we innovatively propose a human-machine collaborative support scheduling system of intelligence information from multi-UAVs based on eye-tracker. Firstly, the target recognition algorithm is applied to the images from the multiple unmanned aerial vehicles(multi-UAVs) to recognize the targets in the images. Then,the support system utilizes the eye tracker to gain the eye-gaze points which are intended to obtain the focused targets in the images. Finally, the heuristic scheduling algorithms take both the attributes of targets and the operator's attention into consideration to obtain the sequence of the images. As the processing time of the images collected by the multi-UAVs is uncertain, however the upper bounds and lower bounds of the processing time are known before. So the processing time of the images is modeled by the interval processing time. The objective of the scheduling problem is to minimize mean weighted completion time. This paper proposes some new polynomial time heuristic scheduling algorithms which firstly schedule the images including the focused targets. We conduct the scheduling experiments under six different distributions. The results indicate that the proposed algorithm is not sensitive to the different distributions of the processing time and has a negligible computational time. The absolute error of the best performing heuristic solution is only about 1%. Then, we incorporate the best performing heuristic algorithm into the human-machine collaborative support systems to verify the performance of the system.

SCHEDULING PROBLEMS - AN OVERVIEW

There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days. These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition, other approaches to solving scheduling problems, for instance approaches based on human factors, prefer the scheduling system to be more flexible in both design and implementation. After discussion of these factors, the authors propose the integration of a different set of criteria for the development of scheduling systems which not only appears to have a better flexibility but also increased customer-focus.