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Synthesis of near-optimal topologically constrained property-based water network using swarm intelligence

CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY 2007年第1期9卷 27-36页

作者： Seingheng, Hul Tan, Raymond R. Auresenia, Joseph Fuchino, Tetsuo Foo, Dominic C. Y. Inst Technol Cambodia Dept Food Chem & Technol Phnom Penh Cambodia De La Salle Univ Dept Chem Engn Manila 1004 Philippines Tokyo Inst Technol Meguro Ku Tokyo 1528550 Japan Univ Notthingham Malaysia Sch Chem & Environm Engn Semenyih 43500 Selangor Malaysia

The sustainability of water resources is one of the major concerns of the world. Industries are finding ways to minimize water costs and to reduce water pollution through efficient use of supplies. One of effective solutions is the use of water pinch technology or process integration techniques. Property integration emerged as the third trend of process integration technique ( aside from energy and mass integration) to solve the problem of water network synthesis by considering physical stream properties such as pH or resistivity. Various techniques have been done to solve this property-based problem. In this paper, mixed integer non-linear programming (MINLP) problems with topological constraints is studied. Nowadays, various evolutionary algorithms are also used to solve such MINLP problems. In this study, particle swarm optimization is used to solve the property integration problem. A comparison is made between this algorithm and commercial genetic algorithm (GA) applications. Particle swarm optimization is observed to perform favorably compared to GA.

关键词： Process integration Property integration mixed integer non-linear programming Particle swarm optimization

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Vehicle routing problem in a kanban controlled supply chain system considering cross-docking strategy

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OPERATIONAL RESEARCH 2020年第4期20卷 2397-2425页

作者： Hasani Goodarzi, Asefeh Zegordi, Seyed Hessameddin Tarbiat Modares Univ Fac Ind & Syst Engn POB 14115-143 Tehran Iran

This paper considers an inventory-routing problem in a distribution network in which kanban is used as a means to implement just-in-time strategy. There are a set of part suppliers and cross-docks in this network, which provide parts for an assembly plant. A novel mixed integer non-linear programming formulation is developed for the problem in which the optimum number of kanbans is determined considering inventory and transportation cost. In the other word, this research aims at reducing the level of inventory and transportation cost in a kanban controlled supply chain system, in which the number of kanbans is to be determined optimally considering demand from suppliers and geographical distribution of them. A fleet of vehicles is applied to transport kanbans from suppliers to the assembly plant via two transportation strategies: direct shipment and shipment through cross-docks (indirect shipment). In the second strategy, it is possible to have routes between suppliers. The proposed problem is NP-hard based on literature, thus a memetic algorithm is introduced to solve it. Solving several examples reveals that the solving method significantly outperforms GAMS/CPLEX in reducing objective value and computational time.

关键词： Just-in-time Kanban Cross-docking Direct shipment mixed integer non-linear programming

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Designing a two-stage model for the resilient agri-food supply chain network under dynamic competition

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BRITISH FOOD JOURNAL 2024年第2期126卷 662-681页

作者： Li, Zhuyue Zhang, Chunxiao Shandong Univ Jinan Peoples R China Ocean Univ China Qingdao Peoples R China

PurposeSupply chain risk management can effectively reduce the loss of retailers. In this regard, retailers need to consider the competition risks of competitors in addition to the disruption risks. This paper designs a resilient retail supply chain network for perishable foods under the dynamic competition to maximize retailer's ***/methodology/approachA two-stage mixed-integer non-linear model is presented for designing the supply chain network. In the first stage, an equilibrium model that considers the characteristics of perishable foods is developed. In the second stage, a mixed integer non-linear programming model is presented to deal with the strategic decisions. Finally, an efficient memetic algorithm is designed to deal with large-scale *** optimal the selection of suppliers, distribution centers and the order allocation are found among the supply chain entities. Considering the perishability of agri-food products, the equilibrium retail price and selling quantity are determined. Through a numerical example, the optimal inventory period under different maximum shelf life and the impact of three resilient strategies on retailer's profit, selling price and selling quantity are *** limitations/implicationsAs for future research, the research can be extended in a number of directions. First, this paper studies the retail supply chain network design problem under competition among retailers. It can be an interesting direction to consider retailers competing with suppliers. Second, the authors can try to linearize the non-linear model and solve the large-scale integer programming problem by exact algorithm. Finally, the freshness of perishable foods gradually declines linearly to zero as the maximum shelf life approaches, and it would be a meaningful attempt to consider the freshness of perishable foods declines ***/valueThis paper innovatively designs the resilient supply chain network for perishabl

关键词： Competitive supply chain network design Supply chain disruptions Supplier selection mixed integer non-linear programming

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An efficient search algorithm for obtaining the optimal replenishment strategies in assembly-type just-in-time supply chain systems

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2018年第2期35卷 118-128页

作者： Yao, Ming-Jong Hsu, Tien-Cheng Natl Chiao Tung Univ Dept Transportat & Logist Management Hsinchu Taiwan Changhua Christian Hosp Informat Syst Dept Changhua Taiwan

An assembly-type just-in-time (JIT) supply chain system is composed of a main serial supply chain and several branching serial supply chains merging to the main supply chain. Under the assumption of constant demand rate, the replenishment problem in the assembly-type JIT supply chain systems can be formulated as a mixed-integer non-linear programming problem. We conduct thorough theoretical analysis on the properties of the objective function value curve in this study. Following our theoretical analysis, we propose a search algorithm that effectively solves an optimal solution. Our numerical experiments show that the average run time of the proposed algorithm grows in a linear order of the problem size, and the proposed algorithm may serve as an efficient solution approach for the decision-maker.

关键词： Kanban supply chain just-in-time mixed integer non-linear programming search algorithm

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An emission constraint capacitor placement and sizing problem in radial distribution systems using modified competitive swarm optimiser approach

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INTERNATIONAL JOURNAL OF AMBIENT ENERGY 2021年第11期42卷 1228-1251页

作者： Das, Soumyabrata Malakar, Tanmoy Natl Inst Technol Dept Elect Engn Silchar India

This paper presents an environment friendly and cost-effective solution procedure to solve the Optimal Capacitor Locations and Sizing (OCLS) problem for power distribution systems. The OCLS problem is formulated as a two-stage mixed integer non-linear programming problem. In the first stage, a new Relative Emission Index based formulation is introduced to select the probable candidate buses for the capacitors. In the second stage, the optimum locations and sizes for the capacitor are determined using basic Competitive Swarm Optimiser (CSO) algorithm. Further, a variant of CSO called 'Opposition based CSO (OCSO)' is proposed and implemented in this work to get improved results. Due to the introduction of opposition based learning phase, three-fourths of the swarm are updated in each cycle in the proposed method, unlike CSO. The annual cost is considered as an objective function in this problem. The capacitor locations and VAr outputs are taken as binary and discrete control variables respectively. The CSO and its proposed modified version 'OCSO' are tested on standard 69 and 118 bus RDS networks with constant power load as well as with practical nonlinear loads. The results obtained with the proposed method are validated by comparing with other reported results in the state-of-art literature and those obtained by other methods.

关键词： Competitive swarm optimiser emission distribution system mixed integer non-linear programming optimum capacitors location and sizing

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Planar expropriation problem with non-rigid rectangular facilities

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COMPUTERS & OPERATIONS RESEARCH 2011年第1期38卷 75-89页

作者： Cakir, Ozan Wesolowsky, George O. McMaster Univ DeGroote Sch Business Hamilton ON L8S 4M4 Canada

In this paper, we introduce the planar expropriation problem with non-rigid rectangular facilities. The facilities considered in this study are two-dimensional facilities of rectangular shape. Moreover, we allow the facility dimensions to be decision variables and introduce the concept of non-rigid facilities. Based on the geometric properties of such facilities, we developed a new formulation for this continuous covering location model which does not require employing distance measures. This model is intended to determine the location and formation of facilities simultaneously. For solving this new model, we proposed a continuous branch-and-bound framework utilizing linear approximations for the tradeoff curve associated with the facility formation alternatives. Further, we developed new problem generation and bounding strategies suitable for our particular problem structure. Computational experience shows that the branch-and-bound procedure we developed performs better than conventional mixed-integer nonlinear programming solvers BARON and SBB for solving this particular location model. (C) 2010 Published by Elsevier Ltd.

关键词： Location analysis Continuous facility location Expropriation location problem Minimal covering location problem Noxious facility location problem Aspect ratio non-rigid facilities mixed integer non-linear programming Branch-and-bound

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New and efficient algorithms for transfer prices and inventory holding policies in two-enterprise supply chains

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JOURNAL OF GLOBAL OPTIMIZATION 2014年第1期60卷 5-24页

作者： Hoai An Le Thi Duc Quynh Tran Univ Lorraine Lab Theoret & Appl Comp Sci LITA EA 3097 F-57045 Metz France

We consider a multi-period problem of fair transfer prices and inventory holding policies in two enterprise supply chains. This problem was formulated as a mixed integer non-linear program by Gjerdrum et al. (Eur J Oper Res 143:582-599, 2002). Existing global optimization methods to solve this problem are computationally expensive. We propose a continuous approach based on difference of convex functions (DC) programming and DC Algorithms (DCA) for solving this combinatorial optimization problem. The problem is first reformulated as a DC program via an exact penalty technique. Afterward, DCA, an efficient local approach in non-convex programming framework, is investigated to solve the resulting problem. For globally solving this problem, we investigate a combined DCA-Branch and Bound algorithm. DCA is applied to get lower bounds while upper bounds are computed from a relaxation problem. The numerical results on several test problems show that the proposed algorithms are efficient: DCA provides a good integer solution in a short CPU time although it works on a continuous domain, and the combined DCA-Branch and Bound finds an -optimal solution for large-scale problems in a reasonable time.

关键词： Supply chain mixed integer non-linear programming Nash bargaining DC programming DCA Branch and bound

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Task Classification for Optimal Offloading and Resource Allocation in Vehicular Edge Computing 8

Task Classification for Optimal Offloading and Resource Allo...

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8th IEEE International Conference on Fog and Mobile Edge Computing (FMEC)

作者： Mubashir, Memona Ahmad, Rizwan Saadat, Ahsan Chaudhry, Saqib Rasool Kiani, Adnan K. Alam, Muhammad Mahtab Natl Univ Sci & Technol NUST Islamabad Pakistan Munster Technol Univ Cork Dept Comp Sci Cork T12 P928 Ireland Nottingham Trent Univ Dept Comp Sci Nottingham NG11 8NS England Tallinn Univ Technol Thomas Johann Seebeck Dept Elect EE-12616 Tallinn Estonia

ISBN: (纸本)9798350316971

Vehicular Edge Computing (VEC) aims to extend cloud service provision to the network edge vehicles, thus reducing back-haul network traffic and service latency. The emergence of computation-intensive tasks in connected, cooperative, and autonomous vehicles is inevitable. Vehicular applications and services generate time-sensitive tasks and require near real-time processing and updates. Executing such computationally intensive tasks on vehicles either leads to high computation latency or unavailability of resources. Recently, VEC has evolved as a popular choice for offloading and used for offloading these complex tasks. However, recent works put an upper limit on task offloading for execution. Moreover, executing a small task over a VEC server causes increased energy consumption and communication latency in a highly dynamic topology. Furthermore, due to the limited computational resources and capacity of the VEC server, it cannot process all tasks when the number of requests is high. Therefore, it is required to have an optimal selection for tasks offloading to solve this problem. A task-centric offloading and optimal resource allocation scheme based on task priority has been proposed in this paper. The proposed approach increases the probability of execution of these tasks on the VEC server as compared to other computation-intensive tasks. The numerical results demonstrate that the proposed work not only minimizes the processing delay but also has increased the percentage of tasks offloaded to the VEC server having higher priority in comparison to baselines.

关键词： Vehicular Edge computing Priority-based-offloading Computation resource allocation mixed integer non-linear programming

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Energy-efficient resource allocation in wireless LANs under non-linear capacity constraints 25

Energy-efficient resource allocation in wireless LANs under ...

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25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (IEEE CAMAD)

作者： Garroppo, Rosario G. Nencioni, Gianfranco Tavanti, Luca Gendron, Bernard Scutella, Maria Grazia Univ Pisa Dept Ingn Informaz Pisa Italy Univ Stavanger Dept Elect Engn & Comp Sci Stavanger Norway Consortium Ubiquitous Technol CUBIT Cascina PI Italy Univ Montreal CIRRELT Montreal PQ Canada Univ Montreal DIRO Montreal PQ Canada Univ Pisa Dept Informat Pisa Italy

ISBN: (数字)9781728163390

ISBN: (纸本)9781728163390

In this paper, we present an approach and an algorithm aimed at minimising the energy consumption of enterprise wireless LANs during periods of low user activity. We act on two network management aspects: powering off some access points (APs), and choosing the level of transmission power of each AP. An efficient technique to allocate the user terminals to the various APs is the key to achieve this goal. The approach has been shaped as an integer programming model with nonlinear constraints, which comes from a general but accurate characterisation of the WLAN system. To solve this model to optimality we present an algorithm named Benders' Decomposition-based Algorithm (BDA). The computational results in realistic scenarios proved the possibility to obtain remarkable power savings.

关键词： Wireless LAN energy efficiency resource allocation optimisation mixed integer non-linear programming green networking network management

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Distribution Network Short Term Scheduling in Smart Grid Context

Distribution Network Short Term Scheduling in Smart Grid Con...

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Silva, M. Morais, H. Vale, Z. A. Polytech Inst Porto ISEP IPP Elect Engn Inst Porto GECAD Knowledge Engn & Decis Support Res Grp P-4200072 Oporto Portugal

ISBN: (纸本)9781457710018

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and "green" operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a mixed integer non-linear programming (MINLP) approach.

关键词： Energy Resources Scheduling Genetic Algorithm mixed integer non-linear programming

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