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A matheuristic for AGV scheduling with battery constraints

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2022年第3期298卷 855-873页

作者： Singh, Nitish Dang, Quang-Vinh Akcay, Alp Adan, Ivo Martagan, Tugce Eindhoven Univ Technol Dept Ind Engn & Innovat Sci POB 513 NL-5600 MB Eindhoven Netherlands

This paper considers the problem of scheduling automated guided vehicles (AGVs) with battery constraints. Each transport request involves a soft time window, and the AGV fleet used to service those requests is heterogeneous with a diverse set of capabilities and travel costs. In contrast to the existing literature, each transport request may require different AGV material handling capabilities (such as lift loads, tow loads, or handle loads with a mounted robot arm), and the AGV batteries can be recharged partially under consideration of a critical battery threshold. The problem is to assign the transport and charging requests to AGVs, sequence the requests, and determine their starting times and the recharging durations of the AGVs with the objective of minimizing a weighted sum of the tardiness costs of transport requests and travel costs of AGVs. A mixed-integer linear programming model is formulated. We also propose a new matheuristic that makes use of an adaptive large neighborhood search algorithm and a linear program to solve industry-size instances. We illustrate the efficacy of our approach with an industry case study using real-world data. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Scheduling Automated guided vehicles Adaptive large neighborhood search mixed-integer linear programming

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Assigning and sequencing storage locations under a two level storage policy: Optimization model and matheuristic approaches x2729

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2022年 108卷 102565-102565页

作者： Lanza, Giacomo Passacantando, Mauro Scutella, Maria Grazia Univ Pisa Dept Comp Sci Largo Bruno Pontecorvo 3 I-56127 Pisa Italy

We deal with a problem which combines storage location assignment with sequencing decisions about the assigned storage locations. Given a set of different product types, with the corresponding storage demand, a set of capacitated storage locations has to be assigned to each product type for the corresponding storing operations. In addition, a suitable sequencing of the assigned storage locations must be devised for each product type, i.e., it has to be decided the ordering with which the storage locations will be filled up during the storing operations. A motivation is that a First-In First-Out (FIFO) picking criterion among storage locations is required per product type. The sequencing established for the assigned storage locations will therefore allow to easily implement the FIFO policy in the successive order picking. Moreover, the selected sequencing also determines the availability of extra storage per product type, on top of pairs of consecutive storage locations along the sequence. The goal is to maximize the storage capacity which remains available after the assignment of the storage locations. We prove the NP-Hardness of the problem and we model it as a constrained multicommodity flow problem on an auxiliary graph. We then propose a mixed-integer linear programming (MILP) model, with some valid inequalities, based on the multicommodity flow formulation. Two relaxations are proposed as well to estimate the quality of the model solutions. Two matheuristic approaches are then designed starting from the MILP model. The proposed methodology is applied to a case study related to a large warehouse with a high stock rotation index in tissue logistics, which motivated our study. Computational results on a wide test bed related to such a real application context show the efficiency and the efficacy of the presented approaches.(c) 2021 Elsevier Ltd. All rights reserved.

关键词： Storage location assignment Storage location sequencing mixed-integer linear programming Multicommodity flows Matheuristic

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Metaheuristics for multiobjective optimization in energy-efficient job shops

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2022年第0期115卷

作者： Gonzalez, Miguel A. Rasconi, Riccardo Oddi, Angelo Univ Oviedo Dept Comp Oviedo Spain ISTC CNR Inst Cognit Sci & Technol Rome Italy

Energy awareness is one of the most relevant research directions in scheduling problems. In this paper we consider the minimization of both the makespan and the energy consumption in the classical job shop scheduling problem. The energy model considered allows several possible states for the machines: off, stand-by, idle, setup and processing. To solve this multi-objective problem we propose an NSGA-II based evolutionary algorithm combined with local search and a heuristic procedure to improve the energy consumption of a given schedule. We also propose an advanced constraint programming (CP) approach as well as a mixed-integer linear programming (MILP) model, to the aim of comparing their performances against those obtained with the NSGA-II. The experimental study is performed against a benchmark set that extends by 41 instances of increasing size, the set tackled in the previous literature against the same problem. The experiments demonstrate the superiority of the NSGA-II algorithm over all other methods, despite the utilization of CP and MILP allows to draw interesting conclusions on the overall solution optimality, revealing that there is still room for further optimization.

关键词： Evolutionary algorithms Heuristic search Constraint programming mixed-integer linear programming Job-shop scheduling Energy aware scheduling

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A Recycling Routing Problem of Broken Bikes With Incentives in Bike Sharing Systems

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IEEE ACCESS 2022年 10卷 106191-106201页

作者： Xu, Guoxun Zou, An Hainan Univ Sch Tourism Haikou 570228 Hainan Peoples R China

In recent years, the truck-based broken bike recycling mode (i.e., dedicated trucks deal with all transportation activities of broken bikes) in bike sharing systems (BSSs) has led to some problems in China, such as BSS operators have no willingness to collect broken bikes from a bike station in time. As a result, many BSSs are in bad condition due to an increase in the number of broken bikes. To solve this problem, many cities in China have started to introduce a new broken bike recycling mode, where some citizens (i.e., sanitation workers, freelancers, volunteers, etc.) are incentivized to participate in recycling activities. To deal with this new recycling mode, a recycling routing problem of broken bikes with incentives in BSSs is proposed, where the recycling operation is performed by citizen participants and a fleet of homogeneous trucks. Participants are incentivized to relocate broken bikes scattered in a BSS to transshipment stations in exchange for monetary rewards, and then these broken bikes are transported from transshipment stations to the depot by trucks. The problem is formulated as a mixed-integer linear programming model to minimize the total operation cost, and an efficient modified tabu search is developed to solve the proposed problem. Experimental results reveal the proposed broken bike recycling mode is beneficial for BSS operators to reduce the operation cost. Experimental results also show the proposed modified tabu search can generate high-quality solutions in short computing times.

关键词： Bicycles Costs Urban areas Search problems Vehicle routing Transportation Routing mixed integer linear programming Bike sharing vehicle routing problem broken bike mixed-integer linear programming tabu search

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Cross-regional integrated transmission of wind power and pumped-storage hydropower considering the peak shaving demands of multiple power grids

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RENEWABLE ENERGY 2022年第0期190卷 1112-1126页

作者： Yuan, Wenlin Xin, Wenpeng Su, Chengguo Cheng, Chuntian Yan, Denghua Wu, Zening Zhengzhou Univ Sch Hydraul Sci & Engn Zhengzhou 450001 Peoples R China Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China China Inst Water Resources & Hydropower Res Water Resources Dept Beijing 100038 Peoples R China

Due to the inherent uncertainty and intermittence of wind power, and the geographical mismatch between the wind power bases and the load demand, the problem of wind curtailment is becoming increasingly serious in China. To promote the consumption of wind power, this paper studies the shortterm operation of a wind farm-pumped storage hydropower plant (WF-PSHP) hybrid system which transmits power to multiple cross-regional power grids through ultra-high-voltage (UHV) transmission lines. In this study, the forecasted error distribution of wind power is fitted using kernel density estimation. An optimization model that considers the peak shaving demands of receiving-end power grids (REPGs) is then established to determine the daily operation of the WF-PSHP system. The hydraulic constraints of the PSHP and individual unit operation constraints are also taken into account to make the model more accurate. To improve the solving efficiency, the original stochastic model is transformed into a deterministic mixed-integer linear programming (MILP) problem through several deterministic conversion and linearization techniques. The real-world case studies demonstrate that the integrated transmission of the WF and PSHP can reduce the peak-valley difference of the REPGs while absorbing large-scale wind power on different typical days in summer and winter.(c) 2021 Elsevier Ltd. All rights reserved.

关键词： Cross-regional integrated transmission Uncertainty of wind power Pumped-storage hydropower plant Peak shaving demand mixed-integer linear programming

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Integrated ethanol and gasoline supply chain planning under environmental constraints: A case study of Brazil

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COMPUTERS & CHEMICAL ENGINEERING 2022年 164卷

作者： Aba, Michael M. Le Roux, Galo A. C. Menezes, Brenno C. Univ Sao Paulo Polyechn Sch Dept Chem Engn Av Prof Luciano GualbertoTrav 3380 BR-05508220 Sao Paulo SP Brazil Hammad Bin Khalifa Univ Coll Sci & Engn Div Engn Management & Decis Sci Qatar Fdn POB 34110 Doha Qatar

The petroleum infrastructure, hydrocarbon costs, and process and distribution networks influence integrated supply chains of mixed biofuels and petroleum derivatives (gasoline and diesel). Furthermore, the seasonality of biomass feedstock poses more complexities when optimizing such a combined bio-fossil-fuel industry. As such, a multi-period mixed-integer linear programming (MILP) planning model proposal addresses this supply chain mixed fuels, whereby strategic and tactical decisions under environmental constraints account for different process design in response to demand fluctuations along the long-term horizon. This work is applied in the bio-fossil-fuel market in Brazil by considering diverse plant configurations and different feedstock with their seasonality. Results yield an optimal facility location and plant configurations optimizing over time the evolution of installed capacities, capacity utilization, carbon credit and emissions profiles. The study involves ethanol streams to be added in the gasoline mix considering exclusive and flex sugarcane and corn-based processing plants. (C) 2022 Elsevier Ltd. All rights reserved.

关键词： Biofuels mixed-integer linear programming Strategic planning Supply chain

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Optimal placement of fixed series compensation and phase shifting transformer in the multi-year generation and transmission expansion planning problem at the pool-based market for maximizing social welfare and reducing the investment costs

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第15期16卷 2959-2976页

作者： Nourizadeh, Heshmatollah Mosallanejad, Ali SetayeshNazar, Mehrdad Shahid Beheshti Univ Dept Elect Engn Tehran Iran

Multi-year generation and transmission expansion planning (MY-G&TEP) is a critical issue in power systems. The present paper considers the optimal placement of Fixed Series Compensation (FSC) and Phase Shifting Transformer (PST) proposes a pool-market-based mathematical model (MY-G&TEP) for maximizing social welfare (SW) and reducing investment costs of transmission lines and new power plants. Following the determination of optimal strategy, the present paper compares the usefulness of PSTs and FSCs in the MY-G&TEP problem in three scenarios. Since MY-G&TEP is a complex hybrid, mixed-integer linear programming (MILP), and nonlinear optimization problem, the YALMIP toolbox and CPLEX solver have been applied to find the optimal solution, a globally optimized solution is obtained. For evaluation, the proposed model has been tested on the IEEE 24-bus and IEEE 57-bus systems, and the simulation results indicate that the installation of PST and FSC not only improves market conditions but also increases the flexibility of MY-G&TEP, and adding these FACTS devices to the studied system leads to an increase in the network's performance and enhancement of objectives of the proposed model.

关键词： PST transmission lines flexible AC transmission systems cost reduction social welfare CPLEX solver pool-based market phase shifting transformer compensation power transmission economics integer programming linear programming power markets power system simulation power transmission planning FSC MY-G&TEP problem MILP investment costs fixed series compensation IEEE 24-bus systems power generation economics power systems mathematical analysis mixed-integer linear programming power transmission lines IEEE 57-bus systems pool-market-based mathematical model power plants nonlinear programming FACTS devices power generation planning transmission expansion planning problem investment nonlinear optimization problem power transformers

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Inventory Positioning in Supply Chain Network: A Service-Oriented Approach

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IEEE ACCESS 2022年 10卷 92986-93002页

作者： Nguyen Trong Tri Duc Pham Duc Tai Buddhakulsomsiri, Jirachai Thammasat Univ Sch Mfg Syst & Mech Engn Sirindhorn Int Inst Technol Khlong Luang 12120 Pathum Thani Thailand

This study develops a mixed-integer linear programming model based on a guaranteed service approach for an inventory positioning problem in a supply chain under the base stock inventory policy. Our proposed model aims to determine appropriate inventory positions and amounts and the optimal service level for the supply chain to minimize the total cost of safety inventory holding and shortage. Two demand scenarios, based on normal and empirical distributions, are investigated. An extensive numerical experiment is conducted to illustrate the applicability and effectiveness of our model, especially under empirical distribution. The experiment features a practical network structure and demand data from an industrial user. Moreover, to further validate the experimental results from the mathematical model, they are compared with the result from a simulation model, which is constructed to imitate the operations of the supply chain. The comparison result indicates that the model solution under the empirical demand distribution is close to the simulation regarding the difference in the total cost (less than 1%). This solution significantly outperforms the model solution under the normal demand, which results in a significant difference in total cost (more than 25%) compared to the simulation.

关键词： Supply chains Safety Mathematical models Costs Uncertainty Stochastic processes inventory control linear programming Base stock policy empirical demand guaranteed service approach inventory positioning mixed-integer linear programming multi-echelon inventory system multiple cycle service levels safety stock placement

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Model-predictive energy management system for thermal batch production processes using online load prediction

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COMPUTERS & CHEMICAL ENGINEERING 2022年 163卷

作者： Fuhrmann, Florian Schirrer, Alexander Kozek, Martin Tech Univ Wien Inst Mech & Mechatron Getreidemarkt 9-BA A-1060 Vienna Austria

Predictive energy management systems (EMS) enable industrial plants to participate in the modern power market and reduce energy cost. In this paper, a novel modular model predictive EMS specifically designed for industrial thermal batch processes is presented. The EMS consists of a two-layer mixed-integer model predictive controller and an online load predictor, and thus solves the main challenges of EMS in industry - high implementation costs and the possible reduction of production reliability. The modular formulation of the optimization problem enables system integrators to implement the EMS without time-consuming modelling tasks and elaborate parameter tuning. The online load predictor estimates the typical pulse-like heat loads of batch processes ensuring both - reliable production and maximal flexibility of the power demand. The utilization of real-time data provides additional robustness against uncertainties caused by human operators. The performance of the EMS is evaluated in a case study of an existing food plant. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Energy management system Model predictive control Online load prediction mixed-integer linear programming Thermal batch processes

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Parametric optimization-based peer-to-peer energy trading among commercial buildings considering multiple energy conversion

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APPLIED ENERGY 2022年第PartB期306卷 118040-118040页

作者： Zhang, Heng Zhang, Shenxi Hu, Xiao Cheng, Haozhong Gu, Qingfa Du, Mengke Shanghai Jiao Tong Univ Key Lab Control Power Transmission & Convers Minist Educ Shanghai 200240 Peoples R China Northeast Elect Power Univ Jilin Jilin Peoples R China State Grid Henan Elect Power Res Inst Zhengzhou Peoples R China State Grid Chaoyang Elect Supply Co Chaoyang Peoples R China

A peer-to-peer energy trading framework of buildings considering multi-energy coupling is presented in this study to improve energy efficiency and achieve cost savings. Microsources, such as photovoltaic and microcombined heat and power, are used to meet electricity and heating demands, while the problem of unbalanced power is solved via the main grid and other peers through peer-to-peer energy trading. All peers aim to maximize their revenue and create trading strategies (i.e., trading period and volume) based on the time-of-use tariff released by the main grid. The trading model established by each peer is a parametric optimization-based problem because each peer must consider the trading willingness of other peers when formulating strategies. A new mixed-integer linear programming problem to maximize total profit can be finally formulated to obtain an equilibrium solution that satisfies all peers. Results show that the proposed peer-to-peer transaction approach can reduce energy bills of buildings. Daily purchased electricity from the main grid decreases by 8.9% through peerto-peer energy trading between different buildings. In addition, compared with the building peer-to-peer transaction that only considers electricity energy management, the amount of purchased electricity from the main network can be reduced by 4.2% a day when multi-energy coupling is considered in peer-to-peer.

关键词： Peer-to-peer Buildings Multi-energy copuling mixed-integer linear programming Parametric optimization

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