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Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices

COMPUTERS & CHEMICAL ENGINEERING 2004年第6-7期28卷 1131-1144页

作者： Chen, CL Lee, WC Natl Taiwan Univ Dept Chem Engn Taipei 10617 Taiwan

A multi-product, multi-stage, and multi-period scheduling model is proposed in this paper to deal with multiple incommensurable goals for a multi-echelon supply chain network with uncertain market demands and product prices. The uncertain market demands are modeled as a number of discrete scenarios with known probabilities, and the fuzzy sets are used for describing the sellers' and buyers' incompatible preference on product prices. The supply chain scheduling model is constructed as a mixed-integer nonlinear programming problem to satisfy several conflict objectives, such as fair profit distribution among all participants, safe inventory levels, maximum customer service levels, and robustness of decision to uncertain product demands, therein the compromised preference levels on product prices from the sellers and buyers point of view are simultaneously taken into account. The inclusion of robustness measures as part of objectives can significantly reduce the variability of objective values to product demand uncertainties. For purpose that a compensatory solution among all participants of the supply chain can be achieved, a two-phase fuzzy decision-making method is presented and, by means of application of it to a numerical example, proved effective in providing a compromised solution in an uncertain multi-echelon supply chain network. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： supply chain management uncertainty robustness multiple objectives mixed-integer nonlinear programming fuzzy optimization

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A SYSTEM-OPTIMUM RELAXATION BASED APPROACH TO DISCRETE NETWORK DESIGN PROBLEMS

A SYSTEM-OPTIMUM RELAXATION BASED APPROACH TO DISCRETE NETWO...

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17th International Conference of Hong-Kong-Society-for-Transportation-Studies (HKSTS)

作者： Wang, Shuaian Meng, Qiang Yang, Hai Univ Wollongong Sch Math & Appl Stat Wollongong NSW 2522 Australia Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore Hong Kong Univ Sci & Technol Dept Civil & Environm Engn Kowloon Hong Kong Peoples R China

ISBN: (纸本)9789881581419

We address the discrete network design problem (DNDP) which determines the optimal number of lanes to add to each candidate link in a road network. We formulate the problem as a bi-level programming model, where the upper level aims to minimize the total travel time via adding new lanes to candidate links and the lower level is a traditional Wardrop user equilibrium (UE) problem. We propose a global optimization method that is based on the system-optimum relaxation of the UE model. Numerical examples are given.

关键词： Discrete network design problem Bi-level programming Traffic equilibrium Network optimization mixed-integer nonlinear programming

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A GA-based search method for the tolerance allocation problem

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ARTIFICIAL INTELLIGENCE IN ENGINEERING 2000年第2期14卷 133-141页

作者： Chen, TC Fischer, GW Chang Jung Univ Dept Informat Management Tainan 711 Taiwan Univ Iowa Dept Ind Engn Iowa City IA 52242 USA

This paper considers nonlinearly constrained tolerance allocation problems in which both tolerance and process selection are to be selected simultaneously so as to minimize the manufacturing cost. The tolerance allocation problem has been studied in the literature for decades, usually using mathematical programming or heuristic optimization approaches;The difficulties encountered for both methodologies are the number of constraints and the difficulty of satisfying the constraints. A penalty-guided genetic algorithm is presented for solving such mixed-integer tolerance allocation problems. It can efficiently and effectively search over promising feasible and infeasible regions to find the feasible optimal or near optimal solution. Genetic results are compared with the results obtained from 12 problems from the literature that dominate the previously mentioned solution techniques. Numerical examples indicate that the genetic algorithms perform well for the tolerance allocation problem considered in this paper. In particular, as reported, solutions obtained by genetic algorithms are as well as or better than the previously best-known solutions. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： tolerance allocation genetic algorithm mixed-integer nonlinear programming

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An exact solution method for reliability optimization in complex systems

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ANNALS OF OPERATIONS RESEARCH 2005年第1-4期133卷 129-148页

作者： Li, D Sun, XL McKinnon, K Chinese Univ Hong Kong Dept Syst Engn & Engn Management Hong Kong Hong Kong Peoples R China Shanghai Univ Dept Math Shanghai 200436 Peoples R China Univ Edinburgh Sch Math Edinburgh EH9 3JZ Midlothian Scotland

Systems reliability plays an important role in systems design, operation and management. Systems reliability can be improved by adding redundant components or increasing the reliability levels of subsystems. Determination of the optimal amount of redundancy and reliability levels among various subsystems under limited resource constraints leads to a mixed-integer nonlinear programming problem. The continuous relaxation of this problem in a complex system is a nonconvex nonseparable optimization problem with certain monotone properties. In this paper, we propose a convexification method to solve this class of continuous relaxation problems. Combined with a branch-and-bound method, our solution scheme provides an efficient way to find an exact optimal solution to integer reliability optimization in complex systems.

关键词： reliability optimization complex system global optimization convexification method mixed-integer nonlinear programming branch-and-bound

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Short-term operation planning of integrated hydrothermal and natural gas systems

Short-term operation planning of integrated hydrothermal and...

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IEEE Lausanne Powertech

作者： Unsihuay, Clodomiro Marangon-Lima, J. W. de Souza, A. C. Zambroni Univ Fed Itajuba Itajuba MG Brazil Univ Fed Itajuba Power & Energy Syst Grp GES Itajuba MG Brazil

ISBN: (纸本)9781424421893

This paper integrates the natural gas and hydrothermal systems in terms of power and gas optimal short-term operations planning and unit commitment. In this paper, the natural gas network model including storages and pipelines are integrated with hydrothermal systems to optimize short-term operation of both systems simultaneously. The proposed model considers the constraints at the hydrothermal system, natural gas extraction, natural gas storage operation and pipeline. The proposed model results in a large-scale mixed-integer nonlinear programming problem where the objective function is to minimize the integrated gas-electricity system operation costs. To solve the integrated electricity-gas optimal short-term planning problem an approach based on Dual Decomposition, Lagrangian Relaxation and Dynamic programming is employed. A didactic integrated hydrothermal and gas system case study is presented. The proposed model shows the importance of the integration of the two systems in terms of operation, planning, security and reliability.

关键词： natural gas systems pipelines network unit commitment scheduling of hydrothermal system primal and dual decomposition mixed-integer nonlinear programming dynamic programming Lagrangian relaxation

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A Fast Solution Approach for Path Optimization in Software-Defined Energy Internet 35

A Fast Solution Approach for Path Optimization in Software-D...

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35th Chinese Control and Decision Conference (CCDC)

作者： Li, Yuting Wu, Jiang Li, Jiaxin Zhou, Yuzhou Gao, Feng Xi An Jiao Tong Univ Syst Engn Inst Xian Peoples R China

ISBN: (纸本)9798350334722

With the rapid development of the Energy Internet, its information subsystem has a large amount of data flow to be transmitted. Since the transmission of data flow requires a large expense to lease the operator network, a stable and economical communication method is critical to the operation of the Energy Internet system. Therefore, this paper proposes a data flow path optimization model for the software-defined energy Internet information subsystem to minimize communication costs while ensuring stable data flow transmission. The method proposed in this paper can be described as a mixed-integer nonlinear programming model. However, due to the inefficiency of commercial solvers for large-scale problems, this paper designs a fast solution approach (ASF) that can effectively improve the efficiency of solving large-scale problems. Numerical tests verify the effectiveness of the proposed algorithm in this paper.

关键词： Energy Internet Software-defined network mixed-integer nonlinear programming network cost minimization a fast solution approach

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Bi-Objective Job-Shop Scheduling Considering Human Fatigue in Cobotic Order Picking Systems: A Case of an Online Grocer 5

Bi-Objective Job-Shop Scheduling Considering Human Fatigue i...

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5th International Conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Vermin, Berry Lance Abbink, David Schulte, Frederik Delft Univ Technol Dept Cognit Robot Mekelweg 2 NL-2628 CD Delft Netherlands Dept Maritime & Transport Technol Mekelweg 2 NL-2628 CD Delft Netherlands

Increasing online retail has resulted in increased automation in order picking systems, leading to new challenges and opportunities in task scheduling. The job-shop scheduling problem is an optimization problem essential in such systems, but existing JSP literature often overlooks workplace fatigue, which harms employees' well-being and costs U.S. employers up to 127 billion annually. In this work, we propose fatigue consideration in the job-shop scheduling problem in a cobotic order picking system to mitigate its negative effects. We present a new bi-objective mixed integer nonlinear programming problem formulation that considers worker fatigue and productivity during schedule optimisation. To put the results of simulated optimisation in perspective, we experimentally validate the fatigue model and scheduling results in a real operation. The mathematical model finds solutions that conventional single-objective optimisation cannot, allowing fractional fatigue distribution improvements more than 4x larger than the decrease in productivity they require in 53% of the considered virtual cases. The experiments show that our predictive fatigue model has an average RMSE of 2.20 kcal/min in estimating energy expenditure rates compared to heart rate measurements. It also shows a low correlation, meaning it is unfit for application. On the other hand, fatigue-conscious schedules show no clear benefit regarding measured and perceived fatigue. However, the scheduling model could also use heart rate measurements that do not show these inaccuracies. Our study highlights the need to further develop and validate the mathematical formulation and fatigue model and extend to other human factors and indirect fatigue effects. (C) 2024 The Authors. Published by Elsevier B.V.

关键词： Order Picking Job-Shop Scheduling Problem Human Factors mixed-integer nonlinear programming Occupational Fatigue Cobotic Order Picking

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The two-level strategy for MINLP synthesis of process flowsheets under uncertainty

The two-level strategy for MINLP synthesis of process flowsh...

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7th International Symposium on Process Systems Engineering

作者： Pintaric, ZN Kravanja, Z Univ Maribor Fac Chem & Chem Engn SI-2000 Maribor Slovenia

This paper presents a two-level strategy for stochastic synthesis of chemical processes under uncertainty with a fixed degree of flexibility by using the mixed-integer nonlinear programming (MINLP) approach. The objective is to develop an automated and robust strategy which could handle nontrivial optimization problems (about 1000 equations and variables with a considerable number of uncertain parameters - up to 30) that, at the present, cannot be solved in a reasonable period of time by using rigorous stochastic optimization methods. To accomplish the task, the nonlinear subproblems at fixed structures have been decomposed into design and operating optimization levels, the former being facilitated by using a direct search method and the latter by using the reduced dimensional stochastic procedure. Two examples are presented to illustrate the robustness and efficiency of the proposed strategy at solving medium- and large-scale problems. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： mixed-integer nonlinear programming synthesis process two-stage two level uncertainty flexibility

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Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices

Multi-objective optimization of multi-echelon supply chain n...

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International Conference on Foundations of Computer-Aided Process Operations

作者： Chen, CL Lee, WC Natl Taiwan Univ Dept Chem Engn Taipei 10617 Taiwan

关键词： supply chain management uncertainty robustness multiple objectives mixed-integer nonlinear programming fuzzy optimization

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Towards Robust Admission Control in Delay-Constrained Routing Problems

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Electronic Notes in Discrete Mathematics 2018年 69卷 45-52页

作者： Frangioni, Antonio Galli, Laura Stea, Giovanni Dipartimento di Informatica Università di Pisa Largo B. Pontecorvo 3 Pisa 56127 Italy Dipartimento di Ingegneria dell'Informazione Università di Pisa Largo Lucio Lazzarino 1 Pisa 56122 Italy

Delay-Constrained Routing (DCR) problems require to route a new flow in a computer network subject to worst-case end-to-end delay guarantees. The delay of a packet flow has three components, one of which is the “queueing delay”, that depends on the scheduling algorithm implemented by the routers of the network. When flows are not independent of each other, i.e., admitting a new flow changes the delay of the existing ones, admission control policies are necessary to ensure that existing flows do not become latency-unfeasible. It has been recently shown that admission control runs contrary to the usual objective function employed in these models, i.e., minimization of the reserved rates, significantly worsening network performance. In this paper we investigate the phenomenon and propose a heuristic way to overcome the problem. © 2018 Elsevier B.V.

关键词： admission control maximum delay constraints mixed-integer nonlinear programming Robustness Routing problems scheduling algorithms Second-Order Cone Programs

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