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5th International Conference on Transportation Information and Safety (ICTIS)

作者： Xing, Jiangbo Wang, Yuhong Ningbo Univ Fac Maritime & Transportat Ningbo Peoples R China

ISBN: (纸本)9781728104898

This paper focuses on the Vessel Schedule Recovery Problem (VSRP) with container flow recovery which aims to find the trade-off between service standards and recovery costs. Firstly, we divide the recovery strategies into three levels for hierarchical management. Second, a MINLP model is presented and can be solved by LINGO. At last, a real-life case study is investigated, and computational results indicate the model can be solved in a few minutes. It is verified that the proposed model is valid.

关键词： Disruption management Liner shipping Vessel schedule recovery problem mixed integer nonlinear programming

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Meta-heuristic algorithms for solving the sustainable agro-food grain supply chain network design problem

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Modern Supply Chain Research and Applications 2020年第3期2卷 161-177页

作者： Ashish Dwivedi Ajay Jha Dhirendra Prajapati Nenavath Sreenu Saurabh Pratap Indian Institute of Technology Delhi New Delhi India Department of Transportation Management University of Petroleum and Energy Studies Dehradun India Mechanical Engineering IIITDM Jabalpur Jabalpur India Management Studies MANIT Bhopal India

Purpose Due to unceasing declination in environment, sustainable agro-food supply chains have become a topic of concern to business, government organizations and customers. The purpose of this study is to examine a problem associated with sustainable network design in context of Indian agro-food grain supply chain. Design/methodology/approach A mixed integer nonlinear programming (MINLP) model is suggested to apprehend the major complications related with two-echelon food grain supply chain along with sustainability aspects (carbon emissions). Genetic algorithm (GA) and quantum-based genetic algorithm (Q-GA), two meta-heuristic algorithms and LINGO 18 (traditional approach) are employed to establish the vehicle allocation and selection of orders set. Findings The model minimizes the total transportation cost and carbon emission tax in gathering food grains from farmers to the hubs and later to the selected demand points (warehouses). The simulated data are adopted to test and validate the suggested model. The computational experiments concede that the performance of LINGO is superior than meta-heuristic algorithms (GA and Q-GA) in terms of solution obtained, but there is trade-off with respect to computational time. Research limitations/implications In literature, inadequate study has been perceived on defining environmental sustainable issues connected with agro-food supply chain from farmer to final distribution centers. A MINLP model has been formulated as practical scenario for central part of India that captures all the major complexities to make the system more efficient. This study is regulated to agro-food Indian industries. Originality/value The suggested network design problem is an innovative approach to design distribution systems from farmers to the hubs and later to the selected warehouses. This study considerably assists the organizations to design their distribution network more efficiently.

关键词： Agro-supply chain Sustainability mixed integer nonlinear programming Meta-heuristics

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Multi-Objective Energy Management in a Residential Area with a P2G-Based Storage System

Multi-Objective Energy Management in a Residential Area with...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Yang, Wentao Liu, Weijia Wen, Fushuan Palu, Ivo Chung, C. Y. Sun, Lei Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China Univ Saskatchewan Dept Elect & Comp Engn Saskatoon SK S7N 5A9 Canada Tallinn Univ Technol Dept Elect Power Engn & Mechatron EE-19086 Tallinn Estonia Hefei Univ Technol Sch Elect Engn & Automat Hefei 230009 Peoples R China

ISBN: (纸本)9781728119816

The energy management in the residential sector, as a basic unit of energy consumption, has received extensive attention in recent years. To address this issue, a residential energy management system (REMS) is proposed, with two objectives considered, i.e., minimizing the costs and maximizing comfort-awareness of end-users. In the framework of the REMS, the economic role of a power-to-gas based storage system (P2GSS) is examined under different operating scenarios. The problem is first formulated as a mixed integer nonlinear programming (MINLP) model and then solved by an iterative decomposition method. In the proposed method, each objective is regarded as an independent sub-problem and refined iteratively, until the deviation comes into an acceptable range. Simulation results of a sample system demonstrate the positive role of the P2GSS in scheduling REMS economically and the effectiveness of the proposed method.

关键词： residential energy management power-to-gas based storage system multi-objective optimization mixed integer nonlinear programming iterative decomposition method

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Solving Multi-objective Dynamic Travelling Salesman Problems by Relaxation 19

Solving Multi-objective Dynamic Travelling Salesman Problems...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Ricciardi, Lorenzo A. Vasile, Massimiliano Univ Strathclyde Glasgow Lanark Scotland

ISBN: (纸本)9781450367486

This paper describes a method to solve Multi-objective Dynamic Travelling Salesman Problems. The problems are formulated as multi-objective hybrid optimal control problems, where the choice of the target destination for each phase is an integer variable. The resulting problem has thus a combinatorial nature in addition to being a multi-objective optimal control problem. The overall solution approach is based on a combination of the Multi Agent Collaborative Search, a population based memetic multi-objective optimisation algorithm, and the Direct Finite Elements Transcription, a direct method for optimal control problems. A relaxation approach is employed to transform the mixed integer problem into a purely continuous problem, and a set of smooth constraints is added in order to ensure that the relaxed variables of the final solution assume an integer value. A special set of smooth constraints is introduced in order to treat the mutually exclusive choices of the targets for each phase. The method is tested on two problems: the first is a motorised Travelling salesman problem described in the literature, the second is a space application where a satellite has to de-orbit multiple debris. For the first problem, the approach is generating better solutions than those reported in the literature.

关键词： Multi-objective Optimisation Global Optimisation Optimal control mixed integer nonlinear programming Memetic Algorithms

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Double-trailer drop-and-pull container drayage problem 31

Double-trailer drop-and-pull container drayage problem

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31st Chinese Control And Decision Conference (CCDC)

作者： Wang, Decheng Zhang, Ruiyou Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9781728101057

This paper considers a double-trailer drop-and-pull container drayage (DTDPCD) problem optimizing the number of employed vehicles. In the DTDPCD problem, a tractor is allowed to carry up to two trailers, trailers can be detached from the tractor during packing unpacking operations. A mixed integer nonlinear programming model is built based on graphical formulation. The model is linearized so that it can be solved using optimizing software such as CPLEX. Computational results based on randomly generated instances show that tractors pulling two trailers can save transportation costs by 13.40% and 29.40%, compared to the single-trailer and stay-with scenarios, respectively.

关键词： Double-trailer Drop-and-pull Container drayage mixed integer nonlinear programming

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FiberSCIP-A Shared Memory Parallelization of SCIP

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INFORMS JOURNAL ON COMPUTING 2018年第1期30卷 11-30页

作者： Shinano, Yuji Heinz, Stefan Vigerske, Stefan Winkler, Michael Zuse Inst Berlin D-14195 Berlin Germany Fair Isaac Germany GmbH D-14195 Berlin Germany GAMS Software GmbH D-14195 Berlin Germany Gurobi GmbH D-14195 Berlin Germany

Recently, parallel computing environments have become significantly popular. In order to obtain the benefit of using parallel computing environments, we have to deploy our programs for these effectively. This paper focuses on a parallelization of SCIP (Solving Constraint integer Programs), which is a mixed-integer linear programming solver and constraint integer programming framework available in source code. There is a parallel extension of SCIP named ParaSCIP, which parallelizes SCIP on massively parallel distributed memory computing environments. This paper describes FiberSCIP, which is yet another parallel extension of SCIP to utilize multi-threaded parallel computation on shared memory computing environments, and has the following contributions: First, we present the basic concept of having two parallel extensions, and the relationship between them and the parallelization framework provided by UG (Ubiquity Generator), including an implementation of deterministic parallelization. Second, we discuss the difficulties in achieving a good performance that utilizes all resources on an actual computing environment, and the difficulties of performance evaluation of the parallel solvers. Third, we present away to evaluate the performance of new algorithms and parameter settings of the parallel extensions. Finally, we demonstrate the current performance of FiberSCIP for solving mixed-integer linear programs (MIPs) and mixed-integer nonlinear programs (MINLPs) in parallel.

关键词： parallel branch-and-bound deterministic parallelism constraint integer programming mixed integer programming mixed integer nonlinear programming SCIP MIP MINLP

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Optimal processing route for the utilization and conversion of municipal solid waste into energy and valuable products

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JOURNAL OF CLEANER PRODUCTION 2018年 174卷 857-867页

作者： Rizwan, Muhammad Saif, Yousef Almansoori, Ali Elkamel, Ali Khalifa Univ Sci & Technol Dept Chem Engn Petr Inst POB 2533 Abu Dhabi U Arab Emirates Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada

A systematic design of municipal solid waste (MSW) management system can lead to identify a promising and/or sustainable way of handling MSW by processing it into energy and valuable products. In this study, a systematic framework is developed for the superstructure-based optimization of MSW processing routes. The proposed superstructure includes the potential technological alternatives (such as recycling, composting, anaerobic digestion with electricity generation, gasification followed by catalytic transformation, gasification with electricity generation, plasma arc gasification with electricity generation, pyrolysis with electricity generation, incineration with electricity generation, and landfill with electricity generation) for producing valuable products from MSW. Based on the developed superstructure, a mixed integer nonlinear programming (MINLP) model is developed to identify the optimal MSW processing pathways considering two different MSW handling scenarios. For ease of the solution, the MINLP model is linearized to its equivalent MILP form, and solved in GAMS. The solution to the optimization problem provides the optimal/promising route for the synthesis of useful products from MSW under chosen economic objective function. The developed framework is applied on a case study of Abu Dhabi Emirate to find the optimal processing pathway for handling and processing of MSW into energy and value-added products. The optimization results show that an integrated pathway comprising of recycling the recyclable components of MSW along with the production of bioethanol from the rest of the waste via gasification followed by catalytic transformation can provide potential economic benefits. A sensitivity analysis is also executed to investigate the effect of key economic and technical parameters on the optimization results. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Municipal solid waste Superstructure-based optimization Sustainable management Waste-to-energy mixed integer nonlinear programming

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Flow Balancing with Uncertain Demand for Automated Package Sorting Centers

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TRANSPORTATION SCIENCE 2018年第1期52卷 210-227页

作者： Novoa, Luis J. Jarrah, Ahmad I. Morton, David P. George Washington Univ Sch Business Dept Decis Sci Washington DC 20052 USA Northwestern Univ Dept Ind Engn & Management Sci Evanston IL 60208 USA

Package carriers use sophisticated automated sorting facilities to efficiently process inbound packages and sort them to their down line destinations. During each of several daily processing windows, primary sorters perform high level sortation of the packages and direct them to one of several secondary sorters that are then used to segregate the packages by their outbound loading destinations. We examine the problem of assigning package destinations to the secondary sorters in a way that balances the workload in the facility, while incorporating the day-to-day fluctuation in package volumes and adhering to the outbound loading capacities of the various workcenters in the facility. We present a general stochastic modeling framework using chance constraints to balance the flows, and robust constraints to model the capacity limits. We propose and evaluate the performance of three alternative mixed integer nonlinear formulations for the problem and determine which is most effective. Significant improvement in package flow balance and loading capacity robustness is shown for the test sorting facilities by comparing the solutions from the proposed new model to those obtained when ignoring, partially or completely, the stochasticity in the package volumes.

关键词： transshipment package carriers postal services automated sortation cross-docking stochastic programming chance constraints robust optimization mixed integer nonlinear programming

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A computational study of primal heuristics inside an MI(NL)P solver

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JOURNAL OF GLOBAL OPTIMIZATION 2018年第1期70卷 189-206页

作者： Berthold, Timo FICO Xpress Optimizat Berlin Germany

Primal heuristics are a fundamental component of state-of-the-art global solvers for mixed integer linear programming (MIP) and mixed integer nonlinear programming (MINLP). In this paper, we investigate the impact of primal heuristics on the overall solution process. We present a computational study, in which we compare the performance of the MIP and MINLP solver SCIP with and without primal heuristics on six test sets with altogether 983 instances from academic and industrial sources. We analyze how primal heuristics affect the solver regarding seven different measures of performance and show that the impact differs by orders of magnitude. We further argue that the harder a problem is to solve to global optimality, the more important the deployment of primal heuristics becomes.

关键词： mixed integer nonlinear programming Primal heuristics Computational study

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Feasibility pump for aircraft deconfliction with speed regulation

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JOURNAL OF GLOBAL OPTIMIZATION 2018年第3期71卷 501-515页

作者： Cafieri, Sonia D'Ambrosio, Claudia Univ Toulouse ENAC F-31055 Toulouse France Ecole Polytech LIX CNRS UMR7161 F-91128 Palaiseau France

We propose Feasibility Pump heuristics for the crucial problem of aircraft conflict avoidance arising in air traffic management. This problem can be modeled as a mixed integer nonlinear optimization problem, whose solution can be very computationally demanding. Feasibility Pump is an iterative algorithm that, at each iteration, solves alternatively two easier subproblems represented by relaxations of the original problem, minimizing the distance between their solutions. We propose in this paper specific formulations for the subproblems to be handled, tailored to the problem at hand. Numerical results show that, on the considered test problems, good-quality, in some cases optimal, feasible solutions are always obtained.

关键词： mixed integer nonlinear programming Feasibility pump Aircraft conflict avoidance Mathematical programming Reformulations Heuristic algorithm

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