scholarly journals Multidepot UAV Routing Problem with Weapon Configuration and Time Window

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Tianren Zhou ◽  
Jiaming Zhang ◽  
Jianmai Shi ◽  
Zhong Liu ◽  
Jincai Huang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Mixed Integer Linear Programming ◽  
Time Window ◽  
Programming Model ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Large Neighborhood Search ◽  
Routing Problem ◽  
Routing Strategy ◽  
Increasing Trend

In recent wars, there is an increasing trend that unmanned aerial vehicles (UAVs) are utilized to conduct military attacking missions. In this paper, we investigate a novel multidepot UAV routing problem with consideration of weapon configuration in the UAV and the attacking time window of the target. A mixed-integer linear programming model is developed to jointly optimize three kinds of decisions: the weapon configuration strategy in the UAV, the routing strategy of target, and the allocation strategy of weapons to targets. An adaptive large neighborhood search (ALNS) algorithm is proposed for solving the problem, which is tested by randomly generated instances covering the small, medium, and large sizes. Experimental results confirm the effectiveness and robustness of the proposed ALNS algorithm.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

scholarly journals An adaptive large neighborhood search heuristic for the planar storage location assignment problem: application to stowage planning for Roll-on Roll-off ships

2020 ◽  
Vol 26 (6) ◽  
pp. 885-912
Author(s):  
Jone R. Hansen ◽  
Kjetil Fagerholt ◽  
Magnus Stålhane ◽  
Jørgen G. Rakke
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Large Neighborhood Search ◽  
Network Graph ◽  
Adaptive Large Neighborhood Search ◽  
Large Neighborhood ◽  
Storage Location ◽  
Stowage Planning ◽  
Stowage Plan

Abstract This paper considers a generalized version of the planar storage location problem arising in the stowage planning for Roll-on/Roll-off ships. A ship is set to sail along a predefined voyage where given cargoes are to be transported between different port pairs along the voyage. We aim at determining the optimal stowage plan for the vehicles stored on a deck of the ship so that the time spent moving vehicles to enable loading or unloading of other vehicles (shifting), is minimized. We propose a novel mixed integer programming model for the problem, considering both the stowage and shifting aspect of the problem. An adaptive large neighborhood search (ALNS) heuristic with several new destroy and repair operators is developed. We further show how the shifting cost can be effectively evaluated using Dijkstra’s algorithm by transforming the stowage plan into a network graph. The computational results show that the ALNS heuristic provides high quality solutions to realistic test instances.

scholarly journals Optimizing Lock Operations and Ship Arrivals through Multiple Locks on Inland Waterways

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hongxu Guan ◽  
Yanmin Xu ◽  
Longhao Li ◽  
Xin Huang
Keyword(s):  
Optimization Problem ◽  
Programming Model ◽  
Waiting Times ◽  
Optimization Method ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Large Neighborhood Search ◽  
Inland Waterways ◽  
Information Availability ◽  
Inland Waterway

Locks are important components of a waterway system. To improve the efficiency of inland waterway transport, it is important to ensure ships passing locks without having to spend unnecessary waiting times at lock entrances. Meanwhile, with the trends towards digitalized and smart waterways, it is also worth investigating how the information availability could contribute to optimizing lock operations and ship arrivals on inland waterways. Therefore, this paper proposes an optimization method to schedule ships’ arrivals and their placements in locks on inland waterways, based on a mixed-integer programming model, and solves the optimization problem with large neighborhood search based heuristics. The optimization objective is threefold: first, optimizing the arrival sequence of ships at the locks; second, maximize the utilization of each lockage operation; and third, reducing the overall time that each ship spends from entering the waterway area till leaving the last lock on the waterway. Simulations are carried out to evaluate the performance of the proposed method.

scholarly journals Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Guangcan Xu ◽  
Qiguang Lyu
Keyword(s):  
Vehicle Routing ◽  
Time Window ◽  
Programming Model ◽  
Distribution Network ◽  
Mixed Integer ◽  
Small Scale ◽  
Routing Problem ◽  
Routing Optimization ◽  
Multiobjective Particle Swarm Optimization ◽  
Vehicle Routing Optimization

In recent years, emergency events have affected urban distribution with increasing frequency. For example, the 2019 novel coronavirus has caused a considerable impact on the supply guarantee of important urban production and living materials, such as petrol and daily necessities. On this basis, this study establishes a dual-objective mixed-integer linear programming model to formulate and solve the cooperative multidepot petrol emergency distribution vehicle routing optimization problem with multicompartment vehicle sharing and time window coordination. As a method to solve the model, genetic variation of multiobjective particle swarm optimization algorithm is considered. The effectiveness of the proposed method is analyzed and verified by first using a small-scale example and then investigating a regional multidepot petrol distribution network in Chongqing, China. Cooperation between petrol depots in the distribution network, customer clustering, multicompartment vehicle sharing, time window coordination, and vehicle routing optimization under partial road blocking conditions can significantly reduce the total operation cost and shorten the total delivery time. Meanwhile, usage of distribution trucks is optimized in the distribution network, that is, usage of single- and double-compartment trucks is reduced while that of three-compartment trucks is increased. This approach provides theoretical support for relevant government departments to improve the guarantee capability of important materials in emergencies and for relevant enterprises to improve the efficiency of emergency distribution.

scholarly journals Vehicle Routing Problem with Transshipment: Mathematical Model and Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Thanapat Leelertkij ◽  
Parthana Parthanadee ◽  
Jirachai Buddhakulsomsiri
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Retail Stores ◽  
Routing Problem ◽  
Hybrid Heuristics ◽  
New Variant ◽  
Problem Instances

This paper presents a new variant of vehicle routing problem with paired transshipment demands (VRPT) between retail stores (customers) in addition to the regular demand from depot to retail stores. The problem originates in a real distribution network of high-end retail department stores in Thailand. Transshipment demands arise for one-order-per-season expensive items, whose inventories at the depot may become shortage after the middle of a season, while they remain available at some retail stores. A transshipment demand is a request for items that need to be picked up from a specific store that has the items and delivered to the store that requests the items. The objective of solving the VRPT is to find delivery routes that can satisfy both regular demands and transshipment demands in the same routes without incurring too much additional transportation distance. A mixed integer linear programming model is formulated to represent the VRPT. Six small problem instances are used to test the model. A hybrid threshold accepting and neighborhood search heuristic is also developed to solve large problem instances of VRPT. The heuristic is further extended to include a forbidden list of transshipment demands that should not be included in the same routes. The purpose is to prevent incurring too much additional distance from satisfying transshipment demands. With the forbidden list, the problem becomes vehicle routing problem with optional transshipment demands (VRPOT). Computational testing shows promising results that indicate effectiveness of the proposed hybrid heuristics as well as the forbidden list.

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