scholarly journals Production Scheduling Optimization of Prefabricated Building Components Based on DDE Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chunguang Chang ◽  
Mengyao Han
Keyword(s):  
Optimization Model ◽  
Production Scheduling ◽  
Precast Concrete ◽  
Optimal Solution ◽  
Production Costs ◽  
Process Time ◽  
Concrete Members ◽  
Hybrid Optimization Model ◽  
Continuous Work ◽  
Process Constraints

At present, the prefabricated construction industry is in a situation of increasing types of prefabricated components and generally high production costs. A hybrid optimization model considering continuity and discreteness for the production of fabricated concrete members is established to minimize production costs through the analysis of the production characteristics of precast concrete members. Under the premise of fully considering the staffing constraints, process constraints, construction period constraints, process constraints, and special process time limits for component production, the production arrangement and staffing of the components are rationalized and optimized. A discrete differential evolution (DDE) algorithm is introduced for such NP-hard problems. The double genetic chromosome coding mode and the active scheduling decoding method are adopted. Based on the improved POX (Precedence Operation Crossover) cross-evolution method, the global evolution operation is carried out, and an interchange-based local search method and continuous work penalty mechanism are designed to find the global optimal solution. The experimental results verify the practicality and effectiveness of the optimization model and algorithm.

scholarly journals Dynamic Optimization Model for Estimating In-Situ Production Quantity of PC Members to Minimize Environmental Loads

2020 ◽  
Vol 12 (19) ◽  
pp. 8202
Author(s):  
Jeeyoung Lim ◽  
Joseph J. Kim
Keyword(s):  
Dynamic Optimization ◽  
Optimization Model ◽  
Co2 Emission ◽  
Precast Concrete ◽  
Environmental Loads ◽  
Concrete Members ◽  
Production Quantity ◽  
Dynamic Optimization Model ◽  
In Situ Production

CO2 emissions account for 80% of greenhouse gases, which lead to the largest contributions to climate change. As the problem of CO2 emission becomes more and more prominent, research on sustainable technologies to reduce CO2 emission among environmental loads is continuously being conducted. In-situ production of precast concrete members has advantages over in-plant production in reducing costs, securing equal or enhanced quality under equal conditions, and reducing CO2 emission. When applying in-situ production to real projects, it is vital to calculate the optimal quantity. This paper presents a dynamic optimization model for estimating in-situ production quantity of precast concrete members subjected to environmental loads. After defining various factors and deriving the objective function, an optimization model is developed using system dynamics. As a result of optimizing the quantity by applying it to the case project, it was confirmed that the optimal case can save 7557 t-CO2 in CO2 emissions and 6,966,000 USD in cost, which resulted in 14.58% and 10.53% for environmental loads and cost, respectively. The model developed here can be used to calculate the quantity of in-situ production quickly and easily in consideration of dynamically changing field conditions.

scholarly journals A Fuzzy Optimization Model for the Berth Allocation Problem and Quay Crane Allocation Problem (BAP + QCAP) with n Quays

2021 ◽  
Vol 9 (2) ◽  
pp. 152
Author(s):  
Edwar Lujan ◽  
Edmundo Vergara ◽  
Jose Rodriguez-Melquiades ◽  
Miguel Jiménez-Carrión ◽  
Carlos Sabino-Escobar ◽  
...  
Keyword(s):  
Optimization Model ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Allocation Problem ◽  
Berth Allocation ◽  
Triangular Fuzzy Numbers ◽  
Berth Allocation Problem ◽  
Arrival Times ◽  
Decision Variables ◽  
Short Time

This work introduces a fuzzy optimization model, which solves in an integrated way the berth allocation problem (BAP) and the quay crane allocation problem (QCAP). The problem is solved for multiple quays, considering vessels’ imprecise arrival times. The model optimizes the use of the quays. The BAP + QCAP, is a NP-hard (Non-deterministic polynomial-time hardness) combinatorial optimization problem, where the decision to assign available quays for each vessel adds more complexity. The imprecise vessel arrival times and the decision variables—berth and departure times—are represented by triangular fuzzy numbers. The model obtains a robust berthing plan that supports early and late arrivals and also assigns cranes to each berth vessel. The model was implemented in the CPLEX solver (IBM ILOG CPLEX Optimization Studio); obtaining in a short time an optimal solution for very small instances. For medium instances, an undefined behavior was found, where a solution (optimal or not) may be found. For large instances, no solutions were found during the assigned processing time (60 min). Although the model was applied for n = 2 quays, it can be adapted to “n” quays. For medium and large instances, the model must be solved with metaheuristics.

scholarly journals Multiobjective Joint Optimization of Production Scheduling and Maintenance Planning in the Flexible Job-Shop Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jianfei Ye ◽  
Huimin Ma
Keyword(s):  
Decision Making ◽  
Optimization Model ◽  
Preventive Maintenance ◽  
Production Scheduling ◽  
Job Shop ◽  
Joint Optimization ◽  
Planning Problem ◽  
Flexible Job Shop ◽  
Maintenance Planning ◽  
Joint Decision

In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.

A fuzzy multi-objective programming optimization model for emergency resource dispatching under equitable distribution principle

2021 ◽  
pp. 1-10
Author(s):  
Zhaoping Tang ◽  
Wenda Li ◽  
Shijun Yu ◽  
Jianping Sun
Keyword(s):  
Optimization Model ◽  
Programming Model ◽  
Ideal Point ◽  
Optimal Solution ◽  
Multi Objective ◽  
Emergency Rescue ◽  
Satisfaction Degree ◽  
Multi Objective Programming ◽  
Parameter Interval ◽  
Objective Programming

In the initial stage of emergency rescue for major railway emergencies, there may be insufficient emergency resources. In order to ensure that all the emergency demand points can be effectively and fairly rescued, considering the fuzzy properties of the parameters, such as the resource demand quantity, the dispatching time and the satisfaction degree, the railway emergency resources dispatching optimization model is studied, with multi- demand point, multi-depot, and multi-resource. Based on railway rescue features, it was proposed that the couple number of relief point - emergency point is the key to affect railway rescue cost and efficiency. Under the premise of the maximum satisfaction degree of quantity demanded at all emergency points, a multi-objective programming model is established by maximizing the satisfaction degree of dispatching time and the satisfaction degree of the couple number of relief point - emergency point. Combined with the ideal point method, a restrictive parameter interval method for optimal solution was designed, which can realize the quick seek of Pareto optimal solution. Furthermore, an example is given to verify the feasibility and effectiveness of the method.

scholarly journals Realtime production scheduling and control systems in smart industry

Impact ◽  
2020 ◽  
Vol 2020 (8) ◽  
pp. 60-61
Author(s):  
Wei Weng
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Production Scheduling ◽  
Production Control ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Scheduling Problems ◽  
Smart Industry ◽  
And Control

For a production system, 'scheduling' aims to find out which machine/worker processes which job at what time to produce the best result for user-set objectives, such as minimising the total cost. Finding the optimal solution to a large scheduling problem, however, is extremely time consuming due to the high complexity. To reduce this time to one instance, Dr Wei Weng, from the Institute of Liberal Arts and Science, Kanazawa University in Japan, is leading research projects on developing online scheduling and control systems that provide near-optimal solutions in real time, even for large production systems. In her system, a large scheduling problem will be solved as distributed small problems and information of jobs and machines is collected online to provide results instantly. This will bring two big changes: 1. Large scheduling problems, for which it tends to take days to reach the optimal solution, will be solved instantly by reaching near-optimal solutions; 2. Rescheduling, which is still difficult to be made in real time by optimization algorithms, will be completed instantly in case some urgent jobs arrive or some scheduled jobs need to be changed or cancelled during production. The projects have great potential in raising efficiency of scheduling and production control in future smart industry and enabling achieving lower costs, higher productivity and better customer service.

scholarly journals Structural Model for Fibre-Reinforced Precast Concrete Sandwich Panels

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Luis Segura-Castillo ◽  
Nicolás García ◽  
Iliana Rodríguez Viacava ◽  
Gemma Rodríguez de Sensale
Keyword(s):  
Structural Model ◽  
Precast Concrete ◽  
Cost Savings ◽  
Production Costs ◽  
Practical Case ◽  
Analysis Model ◽  
Steel Mesh ◽  
Tensile Forces ◽  
Precast Concrete Sandwich Panel ◽  
Precast Elements

Fibre-reinforced concrete (FRC) has been used in numerous types of precast elements around the world, as has been shown that reductions in production costs and time can be obtained; however, there is little experience of this material in Uruguay. Therefore, our study analysed the feasibility of its utilisation in this country. This paper reports on the development of a simple analysis model that is useful for the design of FRC precast elements. The model efficiency was evaluated through its application to a practical case study—vertical precast concrete sandwich panel systems tested by bending. Three different types of reinforcement were analysed: synthetic fibres, metal fibres, and steel mesh. With the developed model, the cost-efficiency of different panel geometries and amounts of reinforcement were evaluated. The model allowed consideration of the contribution of the fibres to withstand internal tensile forces of the panels and therefore be able to substitute for the steel mesh in the panel wythes. It was found that it was possible to optimise panel reinforcement and geometry, thereby reducing wythe thickness. Besides the reduction in production time, it was possible to achieve cost savings of up to 10% by replacing steel mesh with fibres and of more than 20% if the geometry was also modified.

Evolutionary Computing in Engineering Design

2011 ◽  
pp. 167-184
Author(s):  
Rajkumar Roy ◽  
Ashutosh Tiwari ◽  
Yoseph Tafasse Azene ◽  
Gokop Goteng
Keyword(s):  
Engineering Design ◽  
Optimal Solution ◽  
Evolutionary Computing ◽  
Conventional Technique ◽  
Substantial Improvement ◽  
Process Time ◽  
Natural Processes ◽  
The Past ◽  
Performance Requirements ◽  
The One

This chapter presents an overview of the application of evolutionary computing for engineering design. An optimal design may be defined as the one that most economically meets its performance requirements. Optimisation and search methods can assist the designer at all stages of the design process. The past decade has seen a rapid growth of interest in stochastic search algorithms, particularly those inspired by natural processes in physics and biology. Impressive results have been demonstrated on complex practical optimisation of several schools of evolutionary computation. Evolutionary computing unlike conventional technique, have the robustness for producing variety of optimal solutions in a single simulation run, giving wider options for engineering design practitioners to choose from. Despite limitations, the act of finding the optimal solution for optimisation problems has shown a substantial improvement in terms of reducing optimisation process time and cost as well as increasing accuracy. The chapter aims to provide an overview of the application of evolutionary computing techniques for engineering design optimisation and the rational behind why industries and researchers are in favor of using it. It also presents the techniques application trend rise in the past decade.

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