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Optimization of China Crude Oil Transportation Network with Genetic Ant Colony Algorithm

INFORMATION 2015年第3期6卷 467-480页

作者： Wang, Yao Lu, Jing Dalian Maritime Univ Transportat Management Coll Dalian 116026 Liaoning Peoples R China

Taking into consideration both shipping and pipeline transport, this paper first analysed the risk factors for different modes of crude oil import transportation. Then, based on the minimum of both transportation cost and overall risk, a multi-objective programming model was established to optimize the transportation network of crude oil import, and the genetic algorithm and ant colony algorithm were employed to solve the problem. The optimized result shows that VLCC (Very Large Crude Carrier) is superior in long distance sea transportation, whereas pipeline transport is more secure than sea transport. Finally, this paper provides related safeguard suggestions on crude oil import transportation.

关键词： integrated transportation transportation safety multi-objective programming crude oil import transportation network

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Fuzzy multi-objective optimization for optimum allocation in multivariate stratified sampling with quadratic cost and parabolic fuzzy numbers

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2017年第12期87卷 2372-2383页

作者： Gupta, Neha Bari, Abdul SGT Univ Fac Commerce & Management Gurgaon Haryana India Aligarh Muslim Univ Dept Stat & Operat Res Aligarh Uttar Pradesh India

This article deals with the uncertainties in a multivariate stratified sampling problem. The uncertain parameters of the problem, such as stratum standard deviations, measurement costs, travel costs and total budget of the survey, are considered as parabolic fuzzy numbers and the problem is formulated as a fuzzy multi-objective nonlinear programming problem with quadratic cost function. Using -cut, parabolic fuzzy numbers are defuzzified and then the compromise allocations of the problem are obtained by fuzzy programming for a prescribed value of . To demonstrate the utility of the proposed problem a numerical example is solved with the help of [LINGO User?s Guid. Lindo Systems Inc., 1415 North Dayton Street, Chicago,Illinois-60622, (USA), 2013] software and the derived compromise optimum allocation is compared with deterministic and proportional allocations.

关键词： Fuzzy numbers fuzzy programming multi-objective programming compromise allocation stratified sampling travel cost 90C70 90C29 90C30 49M37

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A multi-objective optimization model for a multi-period mobile facility location problem with environmental and disruption considerations

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ANNALS OF OPERATIONS RESEARCH 2022年第2期346卷 1445-1470页

作者： Maliki, Fouad Souier, Mehdi Dahane, Mohammed Ben Abdelaziz, Fouad Mfg Engn Lab Tlemcen MELT Tilimsen Algeria High Sch Appl Sci Tlemcen Tilimsen Algeria High Sch Management Tlemcen Tilimsen Algeria Univ Lorraine LGIPM F-57000 Metz France NEOMA Business Sch Rouen France

The present work addresses a multi-period facility location decision during crisis-Pandemic-situation with highly uncertain demand. Our paper identifies failing distribution centres (DCs) over several periods of time and decides about relocation. Several scenarios arise: DCs can be opened, displaced from one location to another, closed or even reopened during a certain time, using mobile facility. We recommend a multi-objective non-linear mixed-integer mathematical model that identifies, for each period, the best possible location for DCs and their allocation to customers. Our model analyses the trade-off between economic costs and CO2 emissions generated by facilities operations. We suggest a multiobjective approach based on a Non-dominated Sorting Genetic Algorithm II (NSGA-II). Our simulations demonstrate how mobile facility should be managed to ensure a good balance between economic and environmental criteria.

关键词： Facility planning and design multi-objective programming Disruptions Environmental sustainability

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multi-objective optimization for optimum allocation in multivariate stratified sampling with quadratic cost

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2012年第12期82卷 1789-1798页

作者： Khowaja, Saman Ghufran, Shazia Ahsan, M. J. Aligarh Muslim Univ Dept Stat & Operat Res Aligarh Uttar Pradesh India

In stratified sampling, usually the cost function is taken as a linear function of sample sizes n(h). In many practical situations, the linear cost function does not approximate the actual cost incurred adequately. For example, when the cost of travelling between the units selected in the sample within a stratum is significant, instead of a linear cost function, a cost function that is quadratic in root n(h) will be a more close approximation to the actual cost. In this paper, the problem is formulated as multi-objective nonlinear integer programming problem with quadratic cost under three different situations, i.e. complete, partial or null information about the population. A numerical example is also presented to illustrate the computational details.

关键词： stratified sampling travel cost compromise allocation multi-objective programming

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Enumeration technique for set covering problems: a combinatorial approach

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JOURNAL OF INTERDISCIPLINARY MATHEMATICS 2006年第2期9卷 421-430页

作者： Saxena, Ratnesh Rajan Univ Delhi Deen Dayal Upadhyaya Coll Dept Math Karam Pura Delhi 110015 India

Set Covering Problems belong to a class of 0-1 integer programming problems which are NP-complete. The Set Covering Problems have many applications such as location of emergency facilities, truck deliveries, political districting, Air Line Crew Scheduling, Networking and all other programming problems that need the decision variables of the form 0-1. In this paper an enumeration technique is developed to solve the Set Covering Problem using the combinatorial technique. The well-known Breadth First Search technique of graph theory forms the basis of the algorithm. The Set Covering Problems with linear and nonlinear objective functions are discussed. At the end, the concept is extended for multi-objective Set Covering Problem. The algorithms developed in the paper are supported by numerical examples.

关键词： Integer programming problems multi-objective programming combinatroics

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Study on the combination efficiency of industrial enterprises

Study on the combination efficiency of industrial enterprise...

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International Conference on Management and Technology

作者： Ma Zhanxin Zhang Haijuan Cui Xiaohong Inner Mongolia Univ Sch Econ & Management Hohhot 010021 Peoples R China

ISBN: (纸本)9780646480930

Data envelopment analysis(DEA) is an important method to evaluate the efficiency of enterprises, but traditional DEA methods can not evaluate the efficiency of enterprises by some sample units because DEA production possibility sets are not include information of sample units. So we provide a nonparametric approach for evaluating combination efficiency of enterprises by using sample units, then discuss the meaning of combination efficiency and the method for judging combination efficiency. Finally, the combination efficiency of some industrial enterprises is analyzed by using this method.

关键词： combination efficiency data envelopment analysis multi-objective programming production possibility set sample unit

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Interval neutrosophic matrix game-based approach to counter cybersecurity issue

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GRANULAR COMPUTING 2023年第2期8卷 271-292页

作者： Seikh, Mijanur Rahaman Dutta, Shibaji Kazi Nazrul Univ Dept Math Asansol 713340 W Bengal India

Everyone on this planet is now more reliant on information and communication technology. Cybersecurity does the protection from theft and damage of all categories of data that require to be retained top secret. Cybersecurity-related problems that are predicted on lingual data have become the center of attention for researchers in modern times. It is possible to design these uncertain problems by matrix game, where the respective attacker and defender are possibly interpreted as players. Interval-valued neutrosophic numbers (IVNNs) are used as an excellent tool to counter such uncertain circumstances in respect of fuzzy sets/intuitionistic fuzzy sets or ordinary intervals. IVNN addresses topics with a set of interval numbers in the real unit interval. In this paper, cybersecurity-related issues are explored using matrix game, where the respective payoffs are considered as IVNNs. A nonlinear programming approach is presented by constructing two interval-valued multi-objective problems for the players. Then, the subsequent problems are transferred into a pair of auxiliary nonlinear programming models. The weighted average approach is used to solve the reduced problems. A numerical example of the cybersecurity problem in the banking sector is illustrated to show the applicability of the proposed approach. A comparison analysis is performed with existing work to authenticate the feasibility of the proposed approach.

关键词： Interval-valued neutrosophic number Matrix game Cybersecurity multi-objective programming Weighted average approach

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Second-order multi-objective non-differentiable Schaible type model and its duality relation under (K xQ)-C-type-I functions

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INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION 2021年第5期41卷 397-403页

作者： Kumar, Rajnish Alam, Khursheed Dubey, Ramu Sharda Univ Sch Basic Sci & Res Dept Math Greater Noida India Noida Inst Engn & Technol Dept Math Greater Noida India JC Bose Univ Sci & Technol YMCA Dept Math Faridabad 121006 Haryana India

In this article, we constructed second-order (KxQ)-C-type-I functions and also illustrated a nontrivial concrete numerical example for such existing types of functions. Furthermore, we have presented a second-order non-differentiable multi-objective Schaible type dual model with cone objectives as well as cone constraints. Finally, we established duality theorems under (KxQ)-C-I assumptions.

关键词： Non-differentiable [KxQ)-C-second-order type-I multi-objective programming efficient solutions Schaible dual model support functions

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Designing an efficient blood supply chain network in crisis: neural learning, optimization and case study

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ANNALS OF OPERATIONS RESEARCH 2020年第1期289卷 123-152页

作者： Khalilpourazari, Soheyl Soltanzadeh, Shima Weber, Gerhard-Wilhelm Roy, Sankar Kumar Concordia Univ Dept Mech Ind & Aerosp Engn MIAE Montreal PQ Canada Sharif Univ Technol Dept Ind Engn Tehran Iran Poznan Univ Tech Fac Engn Management Ul Strzelecka 11 PL-60965 Poznan Poland Vidyasagar Univ Dept Appl Math Oceanol & Comp Programming Midnapore 721102 W Bengal India Interuniv Res Ctr Enterprise Networks Logist & Tr Montreal PQ Canada Middle East Tech Univ Inst Appl Math TR-06800 Ankara Turkey

In recent years, attention to blood supply chain in disaster circumstances has significantly increased. Disasters, especially earthquakes, have adverse consequences such as destruction, loss of human lives, and undermining the effectiveness of health services. This research considers a six-echelon blood supply chain which consists of donors, blood collection centers (permanent and temporary), regional blood centers, local blood centers, regional hospitals, and local hospitals. For the first time, we considered that helicopters could carry blood from regional hospitals to local hospitals and return injured people that cannot be treated in local hospitals to regional hospitals due to the limited capacity. In addition to the above, different transportations with limited capacities regarded, where the optimal number of required transportations equipment determined after the solution process. This research aims to avoid the worst consequences of a disaster using a neural-learning process to gain from past experiences to meet new challenges. For this aim, this article considers three objective functions that are minimizing total transportation time and cost while minimizing unfulfilled demand. The model implemented based on a real-world case study from the most recent earthquake in the Iran-Iraq border which named the deadliest earthquake of 2017. Based on our results, we learned how to design an efficient blood supply chain that can fulfill hospitals blood demand quickly with the lowest cost using simulation and optimization processes. Moreover, we performed in-depth analyses and provided essential managerial insights at last.

关键词： Blood supply chain Disaster management Humanitarian relief Lexicographic weighted Tchebycheff method Neural learning Operational research multi-objective programming

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multi-objective optimization of crude oil-supply portfolio based on interval prediction data

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ANNALS OF OPERATIONS RESEARCH 2022年第2期309卷 611-639页

作者： Sun, Xiaolei Hao, Jun Li, Jianping Chinese Acad Sci Inst Sci & Dev 15 Zhongguancun Beiyitiao Haidian Dist Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Publ Policy & Management 19A Yuquan Rd Beijing 100049 Peoples R China Univ Chinese Acad Sci Sch Econ & Management 80 Zhongguancun East Rd Haidian Dist Beijing 100190 Peoples R China

The optimization of crude oil-supply portfolio is a hot research issue in energy security, which is closely related to the implementation of national strategy and development of economy. Forecasting the demand of crude oil is the basis for portfolio optimization. Therefore, this paper innovatively introduces the decomposition hybrid interval prediction method and proposes a multi-objective programming model in order to provide decision-making support for the formulation of crude oil-supply portfolio scheme. Under the constraints of volume, price and risk, the minimum cost and risk of importing crude oil are achieved. Furthermore, by introducing optimization parameters and risk preference factors, and setting different scenarios for numerical simulation, the results show that (1) decomposition hybrid prediction methods perform better than single prediction methods. (2) As the optimization parameter increases, costs and risks are significantly decreased. Decision-makers can set large parameters to achieve significant optimization of the objective function. (3) The total cost of imported crude oil fluctuates sharply, while the total risk decreases with the increase of risk preference factors under the different scenarios. (4) The fluctuation of price and risk adjustment factors will cause the change of oil-supply portfolio optimization scheme.

关键词： Energy supply security Country risk Decomposition hybrid methodology Interval prediction multi-objective programming

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