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Late Train-Crew Rescheduling—a Model and a Heuristic Approach

Transportation Research Procedia 2025年 86卷 337-344页

作者： Liyun Yu Carl Henrik Häll Anders Peterson Christiane Schmidt Department of Science and Technology Linköping University Norrköping Sweden

In this paper, we reschedule the duties of train drivers one day before the operation. Due to absent drivers (e.g., because of sick leave), some trains have no driver. Thus, duties on the operation day need to be rescheduled. We start with a feasible crew schedule of the remaining operating drivers, a set of unassigned tasks which were assigned to the absent drivers, and a group of standby drivers with fixed start time, end time, start depot, and end depot. Our aim is to generate a crew schedule with as few cancelled driving tasks and changed tasks as possible. We developed a mixed integer linear programming (MILP) model for short-term crew rescheduling. We also present a Tabu-Search-Based approach with the same objective function and equivalent restrictions of our mathematical model. We compare the results of the MILP model solved by Gurobi 11.0 and of the Tabu-Search-Based approach. Our Tabu-Search-Based approach takes less time and memory occupation to compute a ‘good-enough’ result. We further test the performance of our approach under different circumstances. The data used in the experiments are real data provided by Mälartåg.

关键词： Railway crew rescheduling mixed integer linear programming Tabu search

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Parallel drone scheduling vehicle routing problems with collective drones

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COMPUTERS & OPERATIONS RESEARCH 2024年 163卷

作者： Montemanni, Roberto Dell'Amico, Mauro Corsini, Andrea Univ Modena & Reggio Emilia Dept Sci & Methods Engn Via Amendola 2 I-42122 Reggio Emilia Italy

We study last-mile delivery problems where trucks and drones collaborate to deliver goods to final customers. In particular, we focus on problem settings where either a single truck or a fleet with several homogeneous trucks work in parallel to drones, and drones have the capability of collaborating for delivering missions. This cooperative behavior of the drones, which are able to connect to each other and work together for some delivery tasks, enhance their potential, since connected drone has increased lifting capabilities and can fly at higher speed, overcoming the main limitations of the setting where the drones can only work independently. In this work, we contribute a Constraint programming model and a valid inequality for the version of the problem with one truck, namely the Parallel Drone Scheduling Traveling Salesman Problem with Collective Drones and we introduce for the first time the variant with multiple trucks, called the Parallel Drone Scheduling Vehicle Routing Problem with Collective Drones. For the latter version of the problem, we propose two Constraint programming models and a mixed integer linear programming model. An extensive experimental campaign leads to state-of-the-art results for the problem with one truck and some understanding of the presented models' behavior on the version with multiple trucks. Some insights about future research are finally discussed.

关键词： Parallel Drone Scheduling Vehicle Routing Problems with cooperative drones Constraint programming mixed integer linear programming Parallel Drone Scheduling Traveling Salesman

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Mathematical models and exact algorithms for the Colored Bin Packing Problem

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COMPUTERS & OPERATIONS RESEARCH 2024年 164卷

作者： Borges, Yulle G. F. Schouery, Rafael C. S. Miyazawa, Flavio K. Univ Estadual Campinas Inst Comp BR-13083852 Campinas SP Brazil

This paper focuses on exact approaches for the Colored Bin Packing Problem (CBPP), a generalization of the classical one-dimensional Bin Packing Problem in which each item has, in addition to its length, a color, and no two items of the same color can appear consecutively in the same bin. To simplify modeling, we present a characterization of any feasible packing of this problem in a way that does not depend on its ordering. This allows us to describe the problem with a simple mathematical model. Furthermore, we present four exact algorithms for the CBPP. First, we propose a generalization of Valerio de Carvalho's arc flow formulation for the CBPP using a graph with multiple layers, each representing a color. Second, we present an improved arc flow formulation that uses a more compact graph and has the same linear relaxation bound as the first formulation. And finally, we design two exponential set-partition models based on reductions to a generalized vehicle routing problem, which are solved by a branch-cut-and-price algorithm through VRPSolver. To compare the proposed algorithms, a varied benchmark set with 574 instances of the CBPP is presented. Experimental results show that our best model, the improved arc flow formulation, was able to solve instances of up to 500 items and 37 colors. The set-partition models are also shown to exceed their arc flow counterparts in instances with a very small number of colors.

关键词： Bin Packing Problem Arc flow VRPSolver mixed integer linear programming

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A reformulation approach to resolving the inconsistency of max-min equations on fuzzy algebra

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INTERNATIONAL JOURNAL OF GENERAL SYSTEMS 2024年

作者： Li, Pingke Beijing Univ Technol Coll Econ & Management Beijing Peoples R China

Modelling with fuzzy relations in approximate reasoning is obstructed sometimes by the inconsistency of obtained fuzzy relational equations. This paper tackles the inconsistency resolving problem for a finite system of max-min equations by modifying only the right-hand side vector as slightly as possible with respect to the sum of absolute deviations. It is demonstrated that this problem may be reformulated equivalently as a polynomial-sized mixed integer linear programming problem. Although such a reformulation results in a problem of much larger size than its original compact form, it may be solved to optimality on instances of moderate size or even large size by an off-the-shelf solver for mixed integer linear programming and in some sense does not require a tailored solving method.

关键词： Fuzzy relational equations inconsistency mixed integer linear programming

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Solving a real-life multi-period trailer-truck waste collection problem with time windows

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartA期237卷

作者： Van Engeland, Jens Lavigne, Carolien Belien, Jeroen De Jaeger, Simon Katholieke Univ Leuven Inst Mobil Leuven Belgium Katholieke Univ Leuven Fac Econ & Business Ctr Econ & Corp Sustainabil Campus Brussels Brussels Belgium Katholieke Univ Leuven Fac Econ & Business Operat Management Res Grp Campus Brussels Brussels Belgium

By introducing local recovery networks, regional and local environmental authorities can play an important role in facilitating the circular economy. This paper studies a network design problem that encompasses the recovery of separately collected household waste streams, which are collected in containers at civic amenity sites. We formulate a generic tactical-operational container collection problem that will be solved using a mixed integer linear programming approach. This paper makes both a theoretical and practical contribution. We are the first to study a two container vehicle capacity restriction combined with collection site inventory capacities, time windows, shift break time, and shift duration constraints. The model is applied to a number of real-life test instances and scenarios. The results provide insight in how different combinations of scenarios exactly affect the fleet requirements. This not only includes the number of trucks or information under which circumstances an additional truck would (not) be needed, but also the 12-day collection schedule for the collection crews.

关键词： Container collection Waste management mixed integer linear programming optimization Tactical-operational planning

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Optimal dispatch of BESS-fed virtual power lines under transmission congestion and bulk renewable generation

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ELECTRIC POWER SYSTEMS RESEARCH 2024年 229卷

作者： Nanou, Sotirios I. Psarros, Georgios N. Natl Tech Univ Athens NTUA Sch Elect & Comp Engn 9 Iroon Polytech str Athens 15780 Greece

This paper presents a mixed-integer linear programming (MILP) unit commitment (UC) model for the envisaged virtual power line (VPL) concept, which relies on a coordinated power flow control between two battery energy storage stations (BESS) that are strategically positioned at the supply and demand side of critical transmission line corridors which could exhibit congestion in case of large scale deployment of renewable energy source (RES) stations. The proposed VPL model includes MILP constraints governing the charge/discharge mode of each BESS unit in relation to power flow constraints as well as the availability of RES power. The VPL functionality is further augmented by allocating fast-acting reserves that can be released upon detection of critical line outages, in order to provide virtual power flows through the paired BESS units. As a proof of concept, a 6-bus and the IEEE RTS-79 test system are tested under bulk RES generation. The MILP-UC model is built in GAMS software and detailed UC schedules are assessed in order to demonstrate the potential benefits that VPLs can offer as storage as a transmission-only assets (SATOAs).

关键词： Virtual power line Unit commitment mixed integer linear programming Battery energy storage station

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An integrated mathematical model based on grey optimal ranking for supplier selection considering pandemic situation

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OPSEARCH 2022年第4期59卷 1613-1648页

作者： Chakraborty, Sayan Jain, Akshat Sarmah, S. P. ICFAI Fdn Higher Educ ICFAI Business Sch Hyderabad Dept Operat & IT Hyderabad India Indian Inst Technol Kharagpur Dept Ind & Syst Engn Kharagpur W Bengal India

Optimal selection and allocation of suppliers are crucial decisions for an organization and it becomes more critical when the firm faces disruptive events. The recent outbreak of COVID-19 has led to massive supply disruptions in a supply chain. This paper aims to address the supplier selection and allocation problem of manufacturing firms under pandemic environment. In this study, a novel mixed integer linear programming (MILP) model integrated with grey optimal ranking of suppliers considering factors related to pandemic situation is proposed. The methodology is implemented in two subsequent stages. In the first stage, Grey Relational Analysis is adopted to determine the grey possibility scoring, and in the second stage, a supplier selection model is proposed to integrate the grey scoring to a MILP model to determine optimal allocation of suppliers. The paper presents a numerical study to demonstrate the proposed model and sensitivity analysis is conducted to deduce key managerial insights regarding the factors affecting the allocation under pandemic situation. Further, the illustration demonstrates how the proposed method integrates the expert ranking based approach and the cost minimization approach. The study is generic in nature and provides useful directions for practitioners involved in supplier selection in manufacturing organizations.

关键词： Supplier selection Grey relational analysis mixed integer linear programming COVID-19 pandemic

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A VNS Approach For a Joint Fulfillment and Consolidation Problem in E-commerce

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Transportation Research Procedia 2025年 84卷 89-96页

作者： Kehinde G. Ismaila Adriana F. Gabor Andrei Sleptchenko Maher Maalouf Management Science and Engineering Department Khalifa University Abu Dhabi 127788 UAE Mathematics Department Khalifa University Abu Dhabi 127788 UAE

Recent advances in supply chain and logistics illustrate that consolidation of orders can considerably reduce transportation costs and CO2 emissions. In this paper, we study the impact of consolidation on order fulfillment in e-Commerce. We consider a retailer with an online platform and network of physical stores, who must decide the optimal locations from which to fulfill a set of multi-item orders, as well as the optimal consolidation points for each order. To model the economy of scale obtained by consolidating orders, we consider piecewise-linear concave transportation costs. Our model extends the existing literature by considering multiple orders at a time and stores with limited inventory. We formulate the problem as an MILP and propose a Variable Neighborhood Search (VNS) to find good quality solutions in a short time. We tested the performance of the proposed algorithm on different scenarios, where stores have a varying percentage of overlapping items. Via numerical experiment, we observed a 0.22% average relative increase in cost using VNS for instances with large overlap in items among stores and a 2.36% average relative increase for the other scenarios. On average, the VNS is 16 times faster than the MILP formulation

关键词： Consolidation Multi-Order mixed integer linear programming Variable Neighborhood Search Logistics

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A Maximum Independent Set Method for Scheduling Earth-Observing Satellite Constellations

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JOURNAL OF SPACECRAFT AND ROCKETS 2021年第5期58卷 1416-1429页

作者： Eddy, Duncan Kochenderfer, Mykel J. Stanford Univ Aeronaut & Astronaut Durand Bldg 450 Lomita Mall Stanford CA 94305 USA

Operating Earth-observing satellites requires efficient planning methods that coordinate activities of multiple spacecraft. The satellite task-planning problem entails selecting actions that best satisfy mission objectives for autonomous execution. Task scheduling is often performed by human operators assisted by heuristic or rule-based planning tools. This approach does not efficiently scale to multiple assets as heuristics frequently fail to properly coordinate actions of multiple vehicles over long horizons. Additionally, the problem becomes more difficult to solve for large constellations as the complexity of the problem scales exponentially in the number of requested observations and linearly in the number of spacecraft. It is expected that new commercial optical- and radar-imaging constellations will require automated planning methods to meet stated responsiveness and throughput objectives. This paper introduces a new approach for solving the satellite-scheduling problem by generating an infeasibility-based graph representation of the problem and finding a maximal independent set of vertices for the graph. The approach is tested on a scenario of up to 10,000 requested imaging locations for the SkySat constellation of optical satellites as well as simulated constellations of up to 24 satellites. Performance is compared with contemporary graph-traversal and mixed-integer linear programming approaches. Empirical results demonstrate improvements in the solution time along with the number of scheduled collections beyond baseline methods. For large problems, the maximum independent set approach is able to find a feasible schedule with 8% more collections in 75% less time.

关键词： Satellite Constellations Earth Constellations Synthetic Aperture Radar SkySat mixed integer linear programming Binary Search Algorithm Evolutionary Algorithm Image Resolution North American Aerospace Defense Command

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A mathematical programming approach for optimizing on-specs production for industrial processes under input uncertainty 10th

A mathematical programming approach for optimizing on-specs ...

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10th IFAC Triennial Conference on Manufacturing Modelling, Management and Control (MIM)

作者： Eirinakis, Pavlos Koronakos, Gregory Univ Piraeus Dept Ind Management & Technol Piraeus 18534 Greece Univ Piraeus Dept Informat Piraeus 18534 Greece

Starting from a critical problem in oil refineries, namely on-specs LPG production, we propose a generic mathematical programming approach that incorporates flow and blending constraints for process industries in which impurities must adhere to certain specifications. Moreover, we extend our approach to accommodate the uncertainty that may arise from the level of impurities in the input feed. Copyright (C) 2022 The Authors.

关键词： LPG production quality specifications on-specs recovery mixed integer linear programming Chance Constrained programming process flow network blending

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