scholarly journals Determination of Pavement Rehabilitation Activities through a Permutation Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Sangyum Lee ◽  
Sungho Mun ◽  
Hyungchul Moon
Keyword(s):  
Solution Method ◽  
Programming Model ◽  
Harmony Search ◽  
Optimal Solution ◽  
Decision Models ◽  
Objective Functions ◽  
Mathematical Programming Model ◽  
Pavement Rehabilitation ◽  
Limited Budget

This paper presents a mathematical programming model for optimal pavement rehabilitation planning. The model maximized the rehabilitation area through a newly developed permutation algorithm, based on the procedures outlined in the harmony search (HS) algorithm. Additionally, the proposed algorithm was based on an optimal solution method for the problem of multilocation rehabilitation activities on pavement structure, using empirical deterioration and rehabilitation effectiveness models, according to a limited maintenance budget. Thus, nonlinear pavement performance and rehabilitation activity decision models were used to maximize the objective functions of the rehabilitation area within a limited budget, through the permutation algorithm. Our results showed that the heuristic permutation algorithm provided a good optimum in terms of maximizing the rehabilitation area, compared with a method of the worst-first maintenance currently used in Seoul.

scholarly journals A fuzzy multi-objective linear programming with interval-typed triangular fuzzy numbers

2019 ◽  
Vol 17 (1) ◽  
pp. 607-626 ◽  
Author(s):  
Chunquan Li
Keyword(s):  
Linear Programming ◽  
Fuzzy Numbers ◽  
Programming Model ◽  
Optimal Solution ◽  
Objective Functions ◽  
Triangular Fuzzy Numbers ◽  
Matlab Toolbox ◽  
Multi Objective ◽  
Cut Set ◽  
The Stability

Abstract A multi-objective linear programming problem (ITF-MOLP) is presented in this paper, in which coefficients of both the objective functions and constraints are interval-typed triangular fuzzy numbers. An algorithm of the ITF-MOLP is provided by introducing the cut set of interval-typed triangular fuzzy numbers and the dominance possibility criterion. In particular, for a given level, the ITF-MOLP is converted to the maximization of the sum of membership degrees of each objective in ITF-MOLP, whose membership degrees are established based on the deviation from optimal solutions of individual objectives, and the constraints are transformed to normal inequalities by utilizing the dominance possibility criterion when compared with two interval-typed triangular fuzzy numbers. Then the equivalent linear programming model is obtained which could be solved by Matlab toolbox. Finally several examples are provided to illuminate the proposed method by comparing with the existing methods and sensitive analysis demonstrates the stability of the optimal solution.

scholarly journals A new model for logistic and transportation of fashion goods in the presence of stochastic market demands considering restricted retailers capacity

2019 ◽  
Author(s):  
Aidin Delgoshaei ◽  
Hengameh Norozi ◽  
Abolfazl Mirzazadeh ◽  
Maryam Farhadi ◽  
Golnaz Hooshmand Pakdel ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Case Studies ◽  
Programming Model ◽  
Real Data ◽  
Objective Functions ◽  
Mathematical Programming Model ◽  
Multi Objective ◽  
Scheduling Method ◽  
Stochastic Market

In today’s world, using fashion goods is a vital of human. In this research, we focused on developing a scheduling method for distributing and selling fashion goods in a multi-market/multi-retailer supply chain while the product demands in markets are stochastic. For this purpose, a new multi-objective mathematical programming model is developed where maximizing the profit of selling fashion goods and minimizing delivering time and customer’s dissatisfaction are considered as objective functions. In continue due to the complexity of the problem, a number of metaheuristics are compared and a hybrid of Non-dominated Sorting Genetic Algorithm II (NSGAII) and simulated annealing is selected for solving the case studies. Then, in order to find the best values for input parameters of the algorithm, a Taguchi method is applied. In continue, a number of case studies are selected from literature review and solved by the algorithm. The outcomes are analyzed and it is found that using multi-objective models can find more realistic solutions. Then, the model is applied for a case study with real data from industry and outcomes showed that the proposed algorithm can be successfully applied in practice.

An Interval Approximation Approach for a Multiobjective Programming Model with Fuzzy Objective Functions

2015 ◽  
Vol 23 (06) ◽  
pp. 845-860 ◽  
Author(s):  
M. K. Luhandjula
Keyword(s):  
Multiobjective Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Optimization Under Uncertainty ◽  
Objective Functions ◽  
New Approach ◽  
Different Shapes ◽  
General Goal ◽  
Multiobjective Programming Problems ◽  
Interval Approximation

Research in optimization under uncertainty is alive. It assumes different shapes and forms, all concurring to the general goal of designing effective and efficient tools for handling imprecision in an Optimization setting. In this paper we present a new approach for dealing with multiobjective programming problems with fuzzy objective functions. Similar to many approaches in the literature, our approach relies on the deffuzification of involved fuzzy quantities. Our improvement stem from the choice of a deffuzification operator that captures essential features of fuzzy parameters at hand rather than those that yield single values, leading to a loss of many useful information. Two oracles play a pivotal role in the proposed method. The first one returns a near interval approximation to a given fuzzy number. The other one delivers a Pareto Optimal solution of the resulting multiobjective program with interval coefficient. A numerical example is also provided for the sake of illustration.

Research on the Modeling of Tugboat Assignment Problem in Container Terminal

2012 ◽  
Vol 433-440 ◽  
pp. 1957-1961 ◽  
Author(s):  
Su Wang ◽  
Iko Kaku ◽  
Guo Yue Chen ◽  
Min Zhu
Keyword(s):  
Assignment Problem ◽  
Numerical Experiments ◽  
Solution Method ◽  
Programming Model ◽  
Container Terminal ◽  
Optimal Solution ◽  
Turnaround Time ◽  
Mixed Integer ◽  
Service Capacity ◽  
Decision Making Problem

Tugboat is one kind of important equipment in container terminal to help ships for docking or leaving the berth. Tugboat assignment operation is one of the most important decision making problem because it has an important effect on the turnaround time of ships. In this paper, a mixed-integer programming model combined with scheduling rule is formulated for the Tugboat Assignment Problem (TAP). Then a solution method is provided to obtain the optimal solution of TAP problem. Finally, numerical experiments are executed to illustrate the utility of the model and to analyze the effects of the number and service capacity of tugboats on the turnaround time of ships.

Bi-Objective Optimization of Service-Oriented Location-Pricing Model Using Electromagnetism-Like Mechanism Algorithm

2020 ◽  
Vol 19 (06) ◽  
pp. 1737-1769
Author(s):  
Alireza Alinezhad ◽  
Vahid Hajipour ◽  
Sanaz Hosseinzadeh
Keyword(s):  
Optimal Allocation ◽  
Programming Model ◽  
Waiting Times ◽  
Optimal Number ◽  
Objective Functions ◽  
Mathematical Programming Model ◽  
Multi Objective ◽  
Efficiency And Effectiveness ◽  
Service Oriented ◽  
Total Profit

This paper develops a multi-objective multi-layer location-pricing (MLLP) model with congested facilities in which the facilities act like a classic queuing system. The customers who arrive to this system receive service at all layers in a predetermined order to fulfill their demands. The goal is to determine (1) optimal number of the facilities required at each layer, (2) optimal allocation of customers to facilities, and (3) optimal price of providing service at each layer. The objective functions are to maximize the total profit of the system and to minimize the sum of travel and waiting times, simultaneously. The problem is formulated as a multi-objective nonlinear integer mathematical programming model. Since the problem is hard to be solved analytically, we present a multi-objective meta-heuristic algorithm (MHA) based on an electromagnetism-like mechanism (ELM) as a solution for multi-objective MLLP. This algorithm used an elitist mechanism to strengthen the structure of search engine in order to find better quality solutions. The results indicate the efficiency and effectiveness of the proposed algorithm in comparison with the traditional ELM.

scholarly journals A Framework of Production Planning and Control with Carbon Tax under Industry 4.0

2018 ◽  
Vol 10 (9) ◽  
pp. 3221 ◽  
Author(s):  
Wen-Hsien Tsai ◽  
Yin-Hwa Lu
Keyword(s):  
Production Planning ◽  
Industry 4.0 ◽  
Programming Model ◽  
Carbon Tax ◽  
Optimal Solution ◽  
Production Planning And Control ◽  
Mathematical Programming Model ◽  
Tire Industry ◽  
Planning And Control ◽  
And Control

In recent years, the international community has placed great emphasis on environmental protection issues. The United Nations has also successively enacted relevant laws and regulations to restrain international greenhouse gas emissions and some countries implemented carbon tax levies to reduce air pollution. The tire industry is a manufacturing industry with high pollution and high carbon emissions; therefore, the purpose of this paper is to propose a framework of production planning and control with carbon tax under Industry 4.0 and use the tire industry as the illustrative example. In this framework, the mathematical programming model, with Activity-Based Costing (ABC) and Theory of Constraints (TOC) for production planning, is used to achieve the optimal solution under various production and sale constraints in order to find the optimal product-mix maximizing the profit. On the other hand, Industry 4.0 utilizes new technologies such as 3D printing, robot and automated guided vehicle (AGV) and links all the components in the manufacturing systems by using various sensor systems, Cyber-Physical Systems (CPS) and Internet of Things (IoT) to collect and monitor the activity data of all the components in real-time, to give intelligent responses to various problems that may arise in the factory by the real-time analysis results of cloud computing and big data and to attain the various benefits of Industry 4.0 implementation. The parameters of the mathematical programming model will be updated periodically from the new big data set. In this paper, an illustrative example is used is used to demonstrate the application of the model. From the optimal solution and sensitivity analyses on increasing the raw material’s prices and carbon taxes will affect the profits. This framework can provide a general approach to help companies execute production management in the way of more efficiency, less cost, lower carbon emission and higher quality across the value chain for the tire industry and other industries.

scholarly journals Rank-Based Solution Methods and their Applications in Determination of Non-Dominated Points Set For A Multi-Objective Integer Programming Model

2020 ◽  
Vol 5 (6) ◽  
pp. 1249-1269
Author(s):  
Ali Al-Hasani ◽  
Masar Al-Rabeeah ◽  
Santosh Kumar ◽  
Andrew Eberhard
Keyword(s):  
Integer Programming ◽  
Mathematical Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Optimal Solutions ◽  
Mathematical Programming Model ◽  
Integer Programming Model ◽  
Multi Objective ◽  
Solution Methods ◽  
Single Objective

For any single-objective mathematical programming model, rank-based optimal solutions are computationally difficult to find compared to an optimal solution to the same single-objective mathematical programming model. In this paper, several methods have been presented to find these rank-based optimal solutions and based on them a new rank-based solution method (RBSM) is outlined to identify non-dominated points set of a multi-objective integer programming model. Each method is illustrated by a numerical example, and for each approach, we have discussed its limitations, advantages and computational complexity.

Precision of Weights in Weapon Estimating

2013 ◽  
Vol 774-776 ◽  
pp. 2008-2012
Author(s):  
Zhi Jian Xie ◽  
Cheng Bo Yu
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Mathematical Programming Model

the optimal solution of weights can be solved through the mathematical programming model. The precision of weapon estimating can be improved via substitution of the solution for the subjective or objective weights which are regularly used in system estimate methods.

scholarly journals An Equilibrium Chance-Constrained Multiobjective Programming Model with Birandom Parameters and Its Application to Inventory Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zhimiao Tao ◽  
Jiuping Xu
Keyword(s):  
Genetic Algorithm ◽  
Solution Method ◽  
Multiobjective Programming ◽  
Programming Model ◽  
Simulation Technique ◽  
Equivalent Model ◽  
Objective Functions ◽  
Inventory Problem ◽  
Modified Genetic Algorithm ◽  
Proposed Model

An equilibrium chance-constrained multiobjective programming model with birandom parameters is proposed. A type of linear model is converted into its crisp equivalent model. Then a birandom simulation technique is developed to tackle the general birandom objective functions and birandom constraints. By embedding the birandom simulation technique, a modified genetic algorithm is designed to solve the equilibrium chance-constrained multiobjective programming model. We apply the proposed model and algorithm to a real-world inventory problem and show the effectiveness of the model and the solution method.

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