scholarly journals An optimization approach for green tourist trip design

2021 ◽  
Author(s):  
Ghazaleh Divsalar ◽  
Ali Divsalar ◽  
Armin Jabbarzadeh ◽  
Hadi Sahebi
Keyword(s):  
Computation Time ◽  
Real Data ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Optimization Approach ◽  
Total Cost ◽  
Multi Objective ◽  
Integer Linear Model ◽  
The Cost

Abstract In this paper, the Multi-Objective Multi-Modal Green Tourist Trip Design Problem (MO-MM-GTTDP) as the multi-modal variant of the orienteering problem is investigated. For this problem, a Multi-Objective mixed-integer linear model is formulated, which maximizes the total score of the Trip, minimizes the total cost of the trip as well as the total emission produced in the trip. Various transportation modes are considered for the tourist to choose to move between points of interest (POIs). The tourist choice may be affected by the transportation time and cost. Moreover, choosing the transportation mode will have an impact on the amount of trip pollutants. The cost of visiting POIs, as well as the cost of transportation between POIs, is considered as the total cost of the tour. In addition, a Multi-Objective Variable Neighborhood Search (MOVNS) algorithm is designed to solve instances of this problem. Moreover, a, E - constraint method is implemented in CPLEX and used to evaluate the performance of the presented MOVNS. New instances of the problem are generated based on the existed benchmark OP instances. The conclusion is the high quality of the proposed MOVNS algorithm solutions in practically acceptable computation time (few seconds). Finally, a small case study based on real data on several POIs in the city of Tehran is generated and used to demonstrate the performance of the proposed model and algorithm in practice. For this case study, by using the multi-attribute decision-making method of TOPSIS, the obtained non-dominated solutions are ranked, and the best ones are presented to the tourist.

Pareto Set as a Model for Dispatching Resources in Emergency Centres (Preprint)

2018 ◽  
Author(s):  
Ricardo Guedes ◽  
Vasco Furtado ◽  
Tarcísio Pequeno ◽  
Joel Rodrigues
Keyword(s):  
Operational Research ◽  
Real Data ◽  
Pareto Set ◽  
Multi Objective Optimization ◽  
Pareto Dominance ◽  
Four Dimensions ◽  
Multi Objective ◽  
The Best Approximation ◽  
One Year ◽  
The Cost

UNSTRUCTURED The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.

scholarly journals Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption

2019 ◽  
Vol 11 (11) ◽  
pp. 3127 ◽  
Author(s):  
Tarik Chargui ◽  
Abdelghani Bekrar ◽  
Mohamed Reghioui ◽  
Damien Trentesaux
Keyword(s):  
Energy Consumption ◽  
Programming Model ◽  
Mixed Integer ◽  
Computational Time ◽  
Neighborhood Search ◽  
Optimal Solutions ◽  
Multi Objective ◽  
Sustainable Logistics ◽  
Cross Docking ◽  
Physical Internet

In the context of supply chain sustainability, Physical Internet (PI or π ) was presented as an innovative concept to create a global sustainable logistics system. One of the main components of the Physical Internet paradigm consists in encapsulating products in modular and standardized PI-containers able to move via PI-nodes (such as PI-hubs) using collaborative routing protocols. This study focuses on optimizing operations occurring in a Rail–Road PI-Hub cross-docking terminal. The problem consists of scheduling outbound trucks at the docks and the routing of PI-containers in the PI-sorter zone of the Rail–Road PI-Hub cross-docking terminal. The first objective is to minimize the energy consumption of the PI-conveyors used to transfer PI-containers from the train to the outbound trucks. The second objective is to minimize the cost of using outbound trucks for different destinations. The problem is formulated as a Multi-Objective Mixed-Integer Programming model (MO-MIP) and solved with CPLEX solver using Lexicographic Goal Programming. Then, two multi-objective hybrid meta-heuristics are proposed to enhance the computational time as CPLEX was time consuming, especially for large size instances: Multi-Objective Variable Neighborhood Search hybridized with Simulated Annealing (MO-VNSSA) and with a Tabu Search (MO-VNSTS). The two meta-heuristics are tested on 32 instances (27 small instances and 5 large instances). CPLEX found the optimal solutions for only 23 instances. Results show that the proposed MO-VNSSA and MO-VNSTS are able to find optimal and near optimal solutions within a reasonable computational time. The two meta-heuristics found optimal solutions for the first objective in all the instances. For the second objective, MO-VNSSA and MO-VNSTS found optimal solutions for 7 instances. In order to evaluate the results for the second objective, a one way analysis of variance ANOVA was performed.

scholarly journals Direct Cost of Reprocessing Cotton-woven Surgical Drapes: a Case Study

2015 ◽  
Vol 49 (3) ◽  
pp. 488-494 ◽  
Author(s):  
Mariana Fexina Tomé ◽  
Antônio Fernandes Costa Lima
Keyword(s):  
Human Resources ◽  
Direct Cost ◽  
Financial Resources ◽  
Average Total Cost ◽  
Descriptive Case Study ◽  
Total Cost ◽  
Advantages And Disadvantages ◽  
Cost Of Materials ◽  
The Cost

OBJECTIVE Identify the direct cost of reprocessing double and single cotton-woven drapes of the surgical LAP package. METHOD A quantitative, exploratory and descriptive case study, performed at a teaching hospital. The direct cost of reprocessing cotton-woven surgical drapes was calculated by multiplying the time spent by professionals involved in reprocessing the unit with the direct cost of labor, adding to the cost of materials. The Brazilian currency (R$) originally used for the calculations was converted to US currency at the rate of US$0.42/R$. RESULTS The average total cost for surgical LAP package was US$9.72, with the predominance being in the cost of materials (US$8.70 or 89.65%). It is noteworthy that the average total cost of materials was mostly impacted by the cost of the cotton-woven drapes (US$7.99 or 91.90%). CONCLUSION The knowledge gained will subsidize discussions about replacing reusable cotton-woven surgical drapes for disposable ones, favoring arguments regarding the advantages and disadvantages of this possibility considering human resources, materials, as well as structural, environmental and financial resources.

Measures to Relieve the Stress of Water

2013 ◽  
Vol 361-363 ◽  
pp. 636-639 ◽  
Author(s):  
Shi Kai Duan ◽  
Guo Shi Shen ◽  
Zhen Dong Shan ◽  
Yan Dong ◽  
Kai Zheng ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Shortage ◽  
The United States ◽  
Three Solutions ◽  
Total Cost ◽  
Pros And Cons ◽  
Water Strategy ◽  
The Cost ◽  
Significant Regional Difference

In order to develop realistic water resources strategy, we initially analyze the situation of water resources in the United States which present a significant regional difference. Then on the basis of previous studies, we propose the cost formulas of water storage, movement and desalinization. By analyzing the practical application, along with pros and cons of the above three solutions accordingly, we consider that a comprehensive utilization of these measures will be the best water strategy for America to solve the water shortage problem. Later we apply the conclusion to a case study of Southern California, we propose an optimization model which aims to minimize the total cost of the water strategy, and then use Lingo to solve the problem. Results show that 5.946 billion cubic meters of water by transferring is the best way to make up for the water use gap in 2025 and the total cost is 2.94 billion dollars. Finally, we summarize the strengths and weaknesses of our paper. What needs to be emphasized is that our model can also be adapted into the analysis of other states, which shows great flexibility.

Multi-Objective Optimization in Multi-Attribute and Multi-Unit Combinatorial Reverse Auctions

2017 ◽  
Vol 26 (05) ◽  
pp. 1760016 ◽  
Author(s):  
Shubhashis Kumar Shil ◽  
Samira Sadaoui
Keyword(s):  
Quality Measures ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Solution Quality ◽  
Winner Determination ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Trading Constraints ◽  
Significant Superiority

This study introduces an advanced Combinatorial Reverse Auction (CRA), multi-units, multiattributes and multi-objective, which is subject to buyer and seller trading constraints. Conflicting objectives may occur since the buyer can maximize some attributes and minimize some others. To address the Winner Determination (WD) problem for this type of CRAs, we propose an optimization approach based on genetic algorithms that we integrate with our variants of diversity and elitism strategies to improve the solution quality. Moreover, by maximizing the buyer’s revenue, our approach is able to return the best solution for our complex WD problem. We conduct a case study as well as simulated testing to illustrate the importance of the diversity and elitism schemes. We also validate the proposed WD method through simulated experiments by generating large instances of our CRA problem. The experimental results demonstrate on one hand the performance of our WD method in terms of several quality measures, like solution quality, run-time complexity and trade-off between convergence and diversity, and on the other hand, it’s significant superiority to well-known heuristic and exact WD techniques that have been implemented for much simpler CRAs.

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.

scholarly journals The Study of Prefabricated Construction Methods for Mass Tread Housing Construction. Case Study: Dian Sukolilo Regency Housing, Surabaya

2019 ◽  
Vol 6 (2) ◽  
pp. 49-63
Author(s):  
Stefanie Susanto
Keyword(s):  
Real Data ◽  
Construction Method ◽  
Housing Construction ◽  
Construction Methods ◽  
Simulation Calculation ◽  
The Cost ◽  
Cost Of Construction

This paper discusses the prefabricated construction method by taking a case study of Dian Sukolilo Regency housing construction, Surabaya. Prefabricated construction methods are able to provide faster construction times and better quality. Stages of research will be carried out by processing real data with a simulation calculation approach to obtain the calculation of the budget plan and estimated time of construction using the prefabrication method. The main variables that influence this prefabricated construction method are four namely cost, time, quality and number of units. The increasing number of units will reduce the cost of construction of the construction unit using the prefabrication method. The results of each research calculation will guide the interview to find out the response of the housing developer to the prefabricated construction method whose results will be the conclusion of the study.

scholarly journals Effect of Calculation of Cost of Production on Selling Price of Products Manufacturing Companies in Papua (Case Study CV. Sagita Grafika)

2016 ◽  
Vol 7 (3) ◽  
pp. 6-10
Author(s):  
Mugiati ◽  
Bosta Sihombing
Keyword(s):  
Secondary Data ◽  
Primary Data ◽  
Selling Price ◽  
Manufacturing Companies ◽  
Labor Costs ◽  
Total Cost ◽  
Method Of Calculation ◽  
The Cost ◽  
Costing Analysis

This study aims to determine how the effect of calculating the cost of an order made by the company and the method of calculation of full costing of the product selling price fixing mold. The data used is primary data, order data produced in the period from January 2013 to December 2013, the secondary data obtained from interviews and literature. From these results it can be seen that CV. Sagita Grafika calculate the cost of the product by using the order cost method that produces cost price and the selling price that is incompatible with existing theory, in which the charging of indirect labor and overhead costs shared equally on all types of orders in the amount of Rp. 11.78825 million for indirect labor costs and Rp. 3.1243 million for overhead costs so that volume orders will bear fewer overhead costs equal to the volume of orders more. By using a full costing analysis generated calculation method that the volume of orders that more will earn imposition overhead costs more, because in this calculation loading overhead costs charged by direct labor hours incurred for each order. So that orders with a total volume that many will use a lot of labor hours and vice versa. So in this study that most large orders received charging overhead is the order BS-02 Rp. 31,115,590.92 and most orders received little overhead loading is KK-01 orders in the amount of Rp. 2,208,622.32. Results of a comparison between the cost of the company with the full costing is the total cost of less Rp. 27,499,540.57, the selling price of Rp. 5,866,543.90, while the larger profit generated by using the full costing method that is Rp. 21,632,996.67

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