Models And Heuristics For Crane Scheduling With Temporal And Spatial Constraints

With the development of science and technology,the labor productivity has been increased.But it becomes more and more difficult for the enterprises to improve the profit.Driving in the pursuit of maximum profit,it s the effective mean by raising the logistics transportation level to improve the competitiveness of enterprises.However,due to the restricted number and capacity of transporters,those optimal production schedules are usually excuted inefficienly in actual situation when no sufficient transportation are available.Therefore,research on optimal scheduling of the logistics transportation is helpful to improve the efficiency of transportation and reduce the consumption of the resource and energy so as to make the total cost of production and logistics drop obviously.In this dissertation,firstly we refer to steel plant which is a typical manufacturing system as the background,some optimization problems on crane scheduling for logistics transportation in steelmaking-continuous casting-hot rolling process are studied.Secondly,we refer to container terminal which is a typical logistics system as the bachground,some optimization problems for crane scheduling in container terminal logistics transptation are studied.The research results and core contents are mainly presented in the following four aspects:(1)The optimization problem for crane scheduling problem with spatial and temporal constraints is studied.It is of great significance in steel manufacturing process to link production flow between logistics connection and control production rhythm by cranes.Crane scheduling problem is a multi-machine multi-task NP-hard problem which simultaneously has limits in temporal constraints,spatial constraints and production plan.A model for crane scheduling problem in the steelmaking-refining-continuous casting production process is proposed to fulfill temporal constraints and spatial constraints.Memetic algorithm including task allocation rules and conflicts eliminating rules is conducted to solve it.The results of simulation experiments for the steelmaking-refining-continuous casting production process in a steelmaking plant show that it has good convergence and stability.(2)The optimization problem for crane scheduling problem in slab yard with spatial and temporal constraints is studied.This dissertation researches on crane scheduling problem for slab yard in steel plant.Considering the time and space as well as the hot rolling,a crane scheduling model for slab yard is established.According to the characters of the problem,a memetic algorithm is designed to solve it,which includes of the decoding rules based on Discrete Event Dynamic Simulation(DEDS),adaptive crossover operator,mutation operator and simulate annealing local search after each crossover and mutation.The results of simulation experiments show that it has high convergence speed and stability.(3)The optimization problem for quay crane scheduling problems in container terminal studied.This dissertation researches on quay crane scheduling for unloading operations in container terminal.Considering quay crane work within its time window,an unloading scheduling simulation model is established.According to the characteristics of the unloading scheduling simulation model,a Double List Molecular Structure-based Chemical Reaction Optimization(DLMCRO)algorithm is developed.There are two parts in coding:one is the priority relation of task,and the other is the task-to-quay-node mapping,furthermore we use DEDS to simulate the decoding process.We design four elementary chemical reaction operations against the problem.The results of simulation experiments show that DLMCRO can get a stable and satisfactory solution more quickly than business optimation software CPLEX and GA.And it's proved that the model and algorithm are effective.(4)The optimization problem for berth and quay crane allocation in container terminal is studied.This dissertation researches on a continuous berth and quay crane allocation problem for low carbon container terminal.Considering the constraints of stochastic arrival time and limited truck transportation ability,a multi-objective nonlinear mixed integer programming model is established to minimize carbon emissions and average delay time.A efficient non-dominate sorting genetic algorithm?(ENSGA-?)is designed to deal with this problem.According to the characteristics of the problem,encoding rule and decoding rule based on rolling-horizon simulation,precedence preserving crossover(PPX),multi constraints mutation operator and repair operator have been adopted.The results of simulation experiment show that ENSGA-? can get the satisfied solution more quickly than the non-dominate sorting genetic algorithm ?(NSGAII)and the modified non-dominate sorting genetic algorithm II(MNSGA-?).Moreover,the optimized result not only reduces the carbon emissions,but can also shorten the turnaround.In conclusion,mathematical models are established to solve some optimization problems of crane scheduling for logistics in manufacturing and services.According to the characteristics of mathematical models,this work designs different modern optimization algorithms to solve the problems and provides effective solutions.The validity of the effectiveness of models and algorithms is demonstrated by analyzing a large number of experiments,which provides important reference in solving this type of problem.