scholarly journals An optimization model of the acceptable consensus and its economic significance

Kybernetes ◽  
2016 ◽  
Vol 45 (1) ◽  
pp. 181-206 ◽  
Author(s):  
Zaiwu Gong ◽  
Xiaoxia Xu ◽  
Jeffrey Forrest ◽  
Yingjie Yang
Keyword(s):  
Information Entropy ◽  
Optimization Model ◽  
Optimal Solution ◽  
Limited Resource ◽  
Practical Significance ◽  
Content Type ◽  
Economic Significance ◽  
Consensus Opinion ◽  
Optimization Methodology ◽  
The Stability

Purpose – The purpose of this paper is to construct an optimal resource reallocation model of the limited resource by a moderator for reaching the greatest consensus, and show how to reallocate the limited resources by using optimization methodology once the consensus opinion is reached. Moreover, this paper also devotes to theoretically exploring when or what is the condition that the group decision-making (GDM) system is stable; and when new opinions enter into the GDM, how the level of consensus changes. Design/methodology/approach – By minimizing the differences between the individuals’ opinions and the collective consensus opinion, this paper constructs a consensus optimization model and shows that the objective weights of the individuals are actually the optimal solution to this model. Findings – If all individual deviations of the decision makers (DMs) from the consensus balance each other out, the information entropy theorem shows this GDM is most stable, and economically each individual DM gets the same optimal unit of compensation. Once the consensus opinion is determined and each individual opinion of the DMs is under an acceptable consensus level, the consensus is still acceptable even if additional DMs are added, and the moderator’s cost is still no more than a fixed upper limitation. Originality/value – The optimization model based on acceptable consensus is constructed in this paper, and its economic significance, including the theoretical and practical significance, is emphatically analyzed: it is shown that the weight information of the optimization model carries important economic significance. Besides, some properties of the proposed model are discussed by analyzing its particular solutions: the stability of the consensus system is explored by introducing information entropy theory and variance distribution; in addition, the effect of adding new DMs on the stability of the acceptable consensus system is discussed by analyzing the convergence of consensus level: it is also built up the condition that once the consensus opinion is determined, the consensus degree will not decrease even when additional DMs are added to the GDM.

Iterative problem solving in teams: insights from an agent-based simulation

2016 ◽  
Vol 22 (1/2) ◽  
pp. 2-21 ◽  
Author(s):  
Aleksey Martynov ◽  
Dina Abdelzaher
Keyword(s):  
Problem Solving ◽  
Majority Rule ◽  
Optimal Solution ◽  
Complex Problem ◽  
Practical Significance ◽  
Problem Complexity ◽  
Content Type ◽  
Agent Based ◽  
Model Complex ◽  
Agent Based Simulations

Purpose – This paper aims to evaluate the effect of knowledge overlap, search width and problem complexity on the quality of problem-solving in teams that use the majority rule to aggregate heterogeneous knowledge of the team members. Design/methodology/approach – The paper uses agent-based simulations to model iterative problem-solving by teams. The simulation results are analyzed using linear regressions to show the interactions among the variables in the model. Findings – We find that knowledge overlap, search width and problem complexity interact to jointly impact the optimal solution in the iterative problem-solving process of teams using majority rule decisions. Interestingly, we find that more complex problems require less knowledge overlap. Search width and knowledge overlap act as substitutes, weakening each other’s performance effects. Research limitations/implications – The results suggest that team performance in iterative problem-solving depends on interactions among knowledge overlap, search width and problem complexity which need to be jointly examined to reflect realistic team dynamics. Practical implications – The findings suggest that team formation and the choice of a search strategy should be aligned with problem complexity. Originality/value – This paper contributes to the literature on problem-solving in teams. It is the first attempt to use agent-based simulations to model complex problem-solving in teams. The results have both theoretical and practical significance.

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.

Time-cost optimization in repetitive project scheduling with limited resources

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xin Zou ◽  
Lihui Zhang ◽  
Qian Zhang
Keyword(s):  
Optimization Model ◽  
Cost Optimization ◽  
Residential Building ◽  
Indirect Costs ◽  
Limited Resource ◽  
Project Performance ◽  
Time Cost ◽  
Early Completion ◽  
Solution Quality ◽  
Content Type

PurposeThe purpose of this research is to develop a time-cost optimization model to schedule repetitive projects while considering limited resource availability.Design/methodology/approachThe model is based on the constraint programming (CP) framework; it integrates multiple scheduling characteristics of repetitive activities such as continuous or fragmented execution, atypical activities and coexistence of different modes in an activity. To improve project performance while avoiding inefficient hiring and firing conditions, the strategy of bidirectional acceleration is presented and implemented, which requires keeping regular changes in the execution modes between successive subactivities in the same activity.FindingsTwo case studies involving a real residential building construction project and a hotel refurbishing project are used to demonstrate the application of the proposed model based on four different scenarios. The results show that (1) the CP model has great advantages in terms of solving speed and solution quality than its equivalent mathematical model, (2) higher project performance can be obtained compared to using previously developed models and (3) the model can be easily replicated or even modified to enable multicrew implementation.Originality/valueThe original contribution of this research is presenting a novel CP-based repetitive scheduling optimization model to solve the multimode resource-constrained time-cost tradeoff problem of repetitive projects. The model has the capability of minimizing the project total cost that is composed of direct costs, indirect costs, early completion incentives and late completion penalties.

Research on the variable buyback contract

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tianzhuo Liu ◽  
WangBo Liu ◽  
Feng Yang
Keyword(s):  
Supply Chain ◽  
Stackelberg Game ◽  
Supply Chain Coordination ◽  
Wholesale Price ◽  
Optimal Solution ◽  
Practical Significance ◽  
Content Type ◽  
Current Economic Situation ◽  
Buyback Contract ◽  
System Improvement

Purpose Based on the traditional buyback model, this paper aims to propose a new buyback method – the variable buyback contract – to solve the serious inventory backlog in the current economic situation. Design/methodology/approach In this paper, the authors further study the buyback problem in a two-level supply chain with uncertain demand. Such a problem can be found in many research papers, which also use the Stackelberg game model. They put forward many factors that affect the buyback price, including risk preference, random arrival of consumers, etc. Different from the existing research, the authors propose another factor that may affect supply chain buyback – the retailer's remaining inventory to study the buyback contract. Findings First, the authors found that under the variable buyback contract, there is an optimal retail price, wholesale price and an optimal range of parameter settings for the buyback price. Second, the proposed Pareto-optimal solution for system improvement can achieve supply chain coordination. Third, under some conditions, the variable buyback contract is better than the wholesale price contract and fixed-price buyback contract. Originality/value First, this is the first paper to discuss to measure the buyback price with the retailer's remaining inventory. Second, the proposed buyback contract can help decision-makers to choose the optimal improvement strategies. Third, this contract has a certain practical significance, which can effectively alleviate the current inventory backlog problem.

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 A Multi-Timescale Bilinear Model for Optimization and Control of HVAC Systems with Consistency

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 400 ◽  
Author(s):  
Zelin Nie ◽  
Feng Gao ◽  
Chao-Bo Yan
Keyword(s):  
Optimization Model ◽  
Air Conditioning ◽  
State Of The Art ◽  
Hvac Systems ◽  
Practical Significance ◽  
Hvac System ◽  
Bilinear Model ◽  
Optimization And Control ◽  
And Control ◽  
Slow Timescale

Reducing the energy consumption of the heating, ventilation, and air conditioning (HVAC) systems while ensuring users’ comfort is of both academic and practical significance. However, the-state-of-the-art of the optimization model of the HVAC system is that either the thermal dynamic model is simplified as a linear model, or the optimization model of the HVAC system is single-timescale, which leads to heavy computation burden. To balance the practicality and the overhead of computation, in this paper, a multi-timescale bilinear model of HVAC systems is proposed. To guarantee the consistency of models in different timescales, the fast timescale model is built first with a bilinear form, and then the slow timescale model is induced from the fast one, specifically, with a bilinear-like form. After a simplified replacement made for the bilinear-like part, this problem can be solved by a convexification method. Extensive numerical experiments have been conducted to validate the effectiveness of this model.

Seeking attention: an eye tracking study of in-store merchandise displays

2015 ◽  
Vol 43 (6) ◽  
pp. 561-574 ◽  
Author(s):  
Patricia Huddleston ◽  
Bridget K. Behe ◽  
Stella Minahan ◽  
R. Thomas Fernandez
Keyword(s):  
Visual Attention ◽  
Eye Tracking ◽  
Purchase Intention ◽  
Product Information ◽  
Product Category ◽  
Practical Significance ◽  
Content Type ◽  
First Time ◽  
Tracking Technology

Purpose – The purpose of this paper is to elucidate the role that visual measures of attention to product and information and price display signage have on purchase intention. The authors assessed the effect of visual attention to the product, information or price sign on purchase intention, as measured by likelihood to buy. Design/methodology/approach – The authors used eye-tracking technology to collect data from Australian and US garden centre customers, who viewed eight plant displays in which the signs had been altered to show either price or supplemental information (16 images total). The authors compared the role of visual attention to price and information sign, and the role of visual attention to the product when either sign was present on likelihood to buy. Findings – Overall, providing product information on a sign without price elicited higher likelihood to buy than providing a sign with price. The authors found a positive relationship between visual attention to price on the display sign and likelihood to buy, but an inverse relationship between visual attention to information and likelihood to buy. Research limitations/implications – An understanding of the attention-capturing power of merchandise display elements, especially signs, has practical significance. The findings will assist retailers in creating more effective and efficient display signage content, for example, featuring the product information more prominently than the price. The study was conducted on a minimally packaged product, live plants, which may reduce the ability to generalize findings to other product types. Practical implications – The findings will assist retailers in creating more effective and efficient display signage content. The study used only one product category (plants) which may reduce the ability to generalize findings to other product types. Originality/value – The study is one of the first to use eye-tracking in a macro-level, holistic investigation of the attention-capturing value of display signage information and its relationship to likelihood to buy. Researchers, for the first time, now have the ability to empirically test the degree to which attention and decision-making are linked.

Fusion based learning approach for predicting concrete pouring productivity based on construction and supply parameters

2016 ◽  
Vol 16 (2) ◽  
pp. 185-202 ◽  
Author(s):  
Mojtaba Maghrebi ◽  
Ali Shamsoddini ◽  
S. Travis Waller
Keyword(s):  
Supply Chain ◽  
Production Rate ◽  
Learning Method ◽  
Data Set ◽  
Content Type ◽  
Field Database ◽  
The Stability ◽  
Stable Learning ◽  
Ready Mixed Concrete ◽  
Practical Implications

Purpose The purpose of this paper is to predict the concrete pouring production rate by considering both construction and supply parameters, and by using a more stable learning method. Design/methodology/approach Unlike similar approaches, this paper considers not only construction site parameters, but also supply chain parameters. Machine learner fusion-regression (MLF-R) is used to predict the production rate of concrete pouring tasks. Findings MLF-R is used on a field database including 2,600 deliveries to 507 different locations. The proposed data set and the results are compared with ANN-Gaussian, ANN-Sigmoid and Adaboost.R2 (ANN-Gaussian). The results show better performance of MLF-R obtaining the least root mean square error (RMSE) compared with other methods. Moreover, the RMSEs derived from the predictions by MLF-R in some trials had the least standard deviation, indicating the stability of this approach among similar used approaches. Practical implications The size of the database used in this study is much larger than the size of databases used in previous studies. It helps authors draw their conclusions more confidently and introduce more generalised models that can be used in the ready-mixed concrete industry. Originality/value Introducing a more stable learning method for predicting the concrete pouring production rate helps not only construction parameters, but also traffic and supply chain parameters.

The Correlation between Time and Frequency Dynamic Performance of Control System

2014 ◽  
Vol 628 ◽  
pp. 186-189
Author(s):  
Meng Xiong Zeng ◽  
Jin Feng Zhao ◽  
Wen Ouyang
Keyword(s):  
Control System ◽  
Performance Index ◽  
Dynamic Performance ◽  
Frequency Domain Analysis ◽  
Practical Significance ◽  
Order System ◽  
Time Frequency ◽  
Performance Indexes ◽  
Quantitative Performance ◽  
The Stability

The control system performance requirement was divided into three parts. They were the stability, rapidity and accuracy. The time-frequency domain analysis in the requirements of three performance were measured through quantitative performance index. The mutual restriction of time-frequency performance and system characteristic parameters of normal second order was discussed. The correlation of system time-frequency performance index was established. The relationship between time-frequency performance indexes in standard two order system was extended to higher order system. The mutually constraining and time-frequency correlation between each performance index was obtained by analysis and calculation. The work had been done above had practical significance to reflect the system dynamic performance in different analytical domains.

Sign in / Sign up

Export Citation Format

Share Document