Multi-objective optimization model for airport gate assignment problem

2021 ◽  
Vol 93 (2) ◽  
pp. 311-318
Author(s):  
Ramazan Kursat Cecen
Keyword(s):  
Assignment Problem ◽  
Air Traffic ◽  
Walking Distance ◽  
Content Type ◽  
Multi Objective ◽  
Air Traffic Controllers ◽  
Proposed Model ◽  
Milp Model ◽  
Gate Assignment ◽  
Short Time

Purpose The purpose of this paper is to provide feasible and fast solutions for the multi-objective airport gate assignment problem (AGAP) considering both passenger-oriented and airline-oriented objectives, which is the total walking distance from gate to baggage carousels (TWD) and the total aircraft fuel consumption during taxi operations (TFC). In addition, obtaining feasible and near-optimal solutions in a short time reduces the gate planning time to be spent by air traffic controllers. Design/methodology/approach The mixed integer linear programming (MILP) approach is implemented to solve the multi-objective AGAP. The weighted sum approach technique was applied in the model to obtain non-dominated solutions. Because of the complexity of the problem, the simulated annealing (SA) algorithm was used for the proposed model. The results were compared with baseline results, which were obtained from the algorithm using the fastest gate assignment and baggage carousel combinations without any conflict taking place at the gate assignments. Findings The proposed model noticeably decreased both the TWD and TFC. The improvement of the TWD and TFC changed from 22.8% to 46.9% and from 4.7% to 7.1%, respectively, according to the priorities of the objectives. Additionally, the average number of non-dominated solutions was calculated as 6.94, which presents many feasible solutions for air traffic controllers to manage ground traffic while taking the airline and passenger objectives into consideration. Practical implications The proposed MILP model includes the objectives of different stakeholders: air traffic controllers, passengers and airlines. In addition, the proposed model can provide feasible gate and baggage carousel assignments together in a short time. Therefore, the model creates a flexibility for air traffic controllers to re-arrange assignments if any unexpected situations take place. Originality/value The proposed MILP model combines the TWD and TFC together for the AGAP problem using the SA. Moreover, the proposed model integrates passenger-oriented and airline-oriented objectives together and reveals the relationships between the objectives in only a short time.

A multi-objective supplier selection model for green supply chain network under uncertainty

2018 ◽  
Vol 13 (3) ◽  
pp. 605-625 ◽  
Author(s):  
Mohammad Khalilzadeh ◽  
Hadis Derikvand
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Objective Function Value ◽  
Selection Problem ◽  
Green Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Proposed Model ◽  
Objective Model ◽  
Supplier Selection Problem

Purpose Globalization of markets and pace of technological change have caused the growing importance of paying attention to supplier selection problem. Therefore, this study aims to choose the best suppliers by providing a mathematical model for the supplier selection problem considering the green factors and stochastic parameters. This paper aims to propose a multi-objective model to identify optimal suppliers for a green supply chain network under uncertainty. Design/methodology/approach The objective of this model is to select suppliers considering total cost, total quality parts and total greenhouse gas emissions. Also, uncertainty is tackled by stochastic programming, and the multi-objective model is solved as a single-objective model by the LP-metric method. Findings Twelve numerical examples are provided, and a sensitivity analysis is conducted to demonstrate the effectiveness of the developed mathematical model. Results indicate that with increasing market numbers and final product numbers, the total objective function value and run time increase. In case that decision-makers are willing to deal with uncertainty with higher reliability, they should consider whole environmental conditions as input parameters. Therefore, when the number of scenarios increases, the total objective function value increases. Besides, the trade-off between cost function and other objective functions is studied. Also, the benefit of the stochastic programming approach is proved. To show the applicability of the proposed model, different modes are defined and compared with the proposed model, and the results demonstrate that the increasing use of recyclable parts and application of the recycling strategy yield more economic savings and less costs. Originality/value This paper aims to present a more comprehensive model based on real-world conditions for the supplier selection problem in green supply chain under uncertainty. In addition to economic issue, environmental issue is considered from different aspects such as selecting the environment-friendly suppliers, purchasing from them and taking the probability of defective finished products and goods from suppliers into account.

A multi-objective optimization model for logistic planning in the crisis response phase

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Mahdi Ershadi ◽  
Hossein Shams Shemirani
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Crisis Response ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Proposed Model ◽  
Different Types ◽  
Response Phase ◽  
Logistic Planning

PurposeProper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of injured people, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified injured people.Design/methodology/approachThe main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized injured people in the network. Besides, the total transportation activities of different types of vehicles are considered as another objective function. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize transportation activities as the second objective function while maintaining the optimality of the first objective function.FindingsThe performances of the proposed model were analyzed in different cases and its robust approach for different problems was shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.Practical implicationsThe proposed methodology can be applied to find the best response plan for all crises.Originality/valueIn this paper, we have tried to use a multi-objective optimization model to guide and correct response programs to deal with the occurred crisis. This is important because it can help emergency managers to improve their plans.

The role of natural abilities, intrinsic characteristics, and extrinsic conditions in air traffic controllers’ vocational development

2015 ◽  
Vol 27 (3) ◽  
pp. 241-263 ◽  
Author(s):  
Laura Pylväs ◽  
Petri Nokelainen ◽  
Hilkka Roisko
Keyword(s):  
Test Scores ◽  
Self Regulation ◽  
Target Population ◽  
Air Traffic ◽  
Vocational Development ◽  
Content Type ◽  
Domain Specific ◽  
Air Traffic Controllers ◽  
Specific Factors

Purpose – The purpose of this paper is to apply the Developmental Model of Vocational Excellence (DMVE) in the domain of air traffic control and to describe the characteristics and predictors related to air traffic controllers’ (ATCO) vocational expertise and excellence. Based on DMVE, the study analyses the role of natural abilities (gifts), intrinsic characteristics (self-regulatory abilities) and extrinsic conditions (domain and non-domain specific factors) in ATCOs’ vocational development. Design/methodology/approach – The target population of the multiple case study consisted of ATCOs in Finland (N = 300), of which 28 were interviewed. The interviewees represented four different airports. Initially, three key personnel interviews were conducted to validate the structured theme interview instrument that was subsequently used for the 28 interviews. The data set also included the ATCOs’ aptitude test scores and training records. Employee assessments were used to determine their on-the-job performance level (expertise vs excellence). The research questions were examined using theoretical concept analysis. The qualitative data analysis was conducted with content analysis and Bayesian classification modelling. Findings – The findings indicate that cognitive skills, self-reflection, volition and goal-orientation are considered to be ATCOs’ most important vocational characteristics in addition to interpersonal, intrapersonal and spatial skills. The main differences between the ATCOs representing vocational expertise and those representing vocational excellence were related to self-regulation; motivation and volition in particular proved to be somewhat stronger in the latter group. Research limitations/implications – It was acknowledged that there are limitations in the present study. First, the four airports were not selected randomly. Although they represent different types of airports (and ATCO job profiles) in Finland quite well, future studies should include comparative aspect to airports in other countries. Second, the number of participants (N = 28) in the study was quite small, limiting generalization of the results to the target population (N = 300). Future research on this domain should be extended to include also quantitative measurements, allowing more generalizable results. Third, although the analysis for the research question 3 was based on a technique that is not sensitive to missing values (BCM), missing data in ATCOs’ aptitude test scores, training records and employee assessments added uncertainty to the results. Practical implications – ATCOs’ highly controlled and pre-defined work presents a challenge to work motivation, which is seen as one of the determining factors in safety in air traffic controlling (ATC). In the future, more emphasis should be placed on the prerequisites of professional development such as leadership (human resource management, feedback, employees’ opportunity to influence), working environment (physical and social environment), educational possibilities and career progression, as well as professional benefits (salary and working hours). Originality/value – Although ATC is a fairly studied topic since 1970s, most studies related to ATCOs have concentrated on training, learning on the job, cognitive capacity and processing and stress tolerance. This study extends the emerging research in the field on self-regulation by adopting DMVE to investigate its role, alongside natural abilities and domain and non-domain specific factors, to vocational talent development in different skill acquisition stages.

Multi-objective robust optimization for multi-stage-multi-product agile closed-loop supply chain under uncertainty in the context of circular economy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saeid Jafarzadeh Ghoushchi ◽  
Iman Hushyar ◽  
Kamyar Sabri-Laghaie
Keyword(s):  
Supply Chain ◽  
Robust Optimization ◽  
Circular Economy ◽  
Closed Loop ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Multi Stage ◽  
Proposed Model

PurposeA circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.Design/methodology/approachIn this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.FindingsThe proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.Practical implicationsThis study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.Originality/valueThe main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants.

scholarly journals Multi-objective gate assignment based on robustness in hub airports

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401668858 ◽  
Author(s):  
Hong-Hai Zhang ◽  
Qing-Wen Xue ◽  
Yu Jiang
Keyword(s):  
Optimization Algorithm ◽  
New Method ◽  
Optimal Solutions ◽  
Interval Time ◽  
Multi Objective ◽  
Assignment Model ◽  
Proposed Model ◽  
Simulation Results ◽  
Gate Assignment

To enhance the robustness of the gate assignment, reduce the possibility of flight conflict, and improve the quality of passenger services, a multi-objective gate assignment model is proposed by minimizing flight conflict probability and number of flights assigned to aprons. The biogeography-based optimization algorithm is used to solve the proposed model with a new method for estimating the conflict probability. The simulation results show that the ratio of interval time of two flights assigned to the same gate between 60 and 120 min is as high as 82% when the rate of the flights assigned to aprons is controlled below 0.4. This means that the robustness increases greatly, and the probability of flight conflicts decreases, which is beneficial to the implement of flight assignment plan. In addition, the biogeography-based optimization algorithm is more effective to solve the proposed model and very easy to find out the optimal solutions.

Study on an airport gate assignment method based on improved ACO algorithm

Kybernetes ◽  
2018 ◽  
Vol 47 (1) ◽  
pp. 20-43 ◽  
Author(s):  
Wu Deng ◽  
Meng Sun ◽  
Huimin Zhao ◽  
Bo Li ◽  
Chunxiao Wang
Keyword(s):  
Optimization Model ◽  
Optimal Solution ◽  
Ant Colony ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Assignment Method ◽  
Local Optimal Solution ◽  
Gate Assignment ◽  
Update Strategy

Purpose This study aims to propose a new airport gate assignment method to effectively improve the comprehensive operation capacity and efficiency of hub airport. Gate assignment is one of the most important tasks for airport ground operations, which assigns appropriate airport gates with high efficiency reasonable arrangement. Design/methodology/approach In this paper, on the basis of analyzing the characteristics of airport gates and flights, an efficient multi-objective optimization model of airport gate assignment based on the objectives of the most balanced idle time, the shortest walking distances of passengers and the least number of flights at apron is constructed. Then an improved ant colony optimization (ICQACO) algorithm based on the ant colony collaborative strategy and pheromone update strategy is designed to solve the constructed model to fast realize the gate assignment and obtain a rational and effective gate assignment result for all flights in the different period. Findings In the designed ICQACO algorithm, the ant colony collaborative strategy is used to avoid the rapid convergence to the local optimal solution, and the pheromone update strategy is used to quickly increase the pheromone amount, eliminate the interference of the poor path and greatly accelerate the convergence speed. Practical implications The actual flight data from Guangzhou Baiyun airport of China is selected to verify the feasibility and effectiveness of the constructed multi-objective optimization model and the designed ICQACO algorithm. The experimental results show that the designed ICQACO algorithm can increase the pheromone amount, accelerate the convergence speed and avoid to fall into the local optimal solution. The constructed multi-objective optimization model can effectively improve the comprehensive operation capacity and efficiency. This study is a very meaningful work for airport gate assignment. Originality/value An efficient multi-objective optimization model for hub airport gate assignment problem is proposed in this paper. An improved ant colony optimization algorithm based on ant colony collaborative strategy and the pheromone update strategy is deeply studied to speed up the convergence and avoid to fall into the local optimal solution.

An efficient stochastic programming approach for solving integrated multi-objective transportation and inventory management problem using goodness of fit

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Srikant Gupta ◽  
Sachin Chaudhary ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Supply Chain ◽  
Transportation Cost ◽  
Programming Approach ◽  
Main Concern ◽  
Management Problem ◽  
Order Allocation ◽  
Inventory Cost ◽  
Content Type ◽  
Multi Objective ◽  
Proposed Model

PurposeLogistics is the part of the supply chain (SC) that plans, executes and handles forward and reverse movement and storage of products, services and related information, in order to respond to customers' needs effectively and efficiently. The main concern for logistics is to ensure that the correct product is placed at the right time. This paper introduces a linear model of shipping focused on decision-making, which includes configuration of shipping network, choosing of transport means and transfer of individual customer shipments through a particular transport system.Design/methodology/approachIn this study, authors try to address the problem of supply chain network (SCN) where the primary goal is to determine the appropriate order allocation of products from different sources to different destinations. They also seek to minimize total transportation cost and inventory cost by simultaneously determining optimal locations, flows and shipment composition. The formulated problem of getting optimal allocation turns out to be a problem of multi-objective programming, and it is solved by using the max-addition fuzzy goal programming approach, for obtaining optimal order allocation of products. Furthermore, the problem demand and supply parameters have been considered random in nature, and the maximum likelihood estimation approach has been used to assess the unknown probabilistic distribution parameters with a specified probability level (SPL).FindingsA case study has also been applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. Results of this study are very relevant for the manufacturing sector in particular, for those facing logistics issues in SCN. It enables researchers and managers to cope with various types of uncertainty and logistics risks associated with SCN.Research limitations/implicationsThe principal contribution of the proposed model is the improved modelling of transportation and inventory, which are affected by different characteristics of SCN. To demonstrate computational information of the suggested methods and proposed model, a case illustration of SCN is provided. Also, environmentalism is increasingly becoming a significant global concern. Hence, the concept proposed could be extended to include environmental aspects as an objective function or constraint.Originality/valueEfficient integration of logistical cost components, such as transportation costs, inventory costs, with mathematical programming models is an important open issue in logistics optimization. This study expands conventional facility location models to incorporate a range of logistic system elements such as transportation cost and different types of inventory cost, in a multi-product, multi-site network. The research is original and is focused on case studies of real life.

Sign in / Sign up

Export Citation Format

Share Document