Industrial and tramp ship routing problems: Closing the gap for real-scale instances

Homsi, Gabriel; Martinelli, Rafael; Vidal, Thibaut; Fagerholt, Kjetil

doi:10.1016/j.ejor.2019.11.068

Cited by 24 publications

(19 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed algorithm has educational value by showing the connection between two problems, MST and TSP, of which one can be solved optimally using greedy heuristics while the other is known to be NP hard problem. The result of the algorithm can also be used as initial solution for local search heuristic or optimal algorithms like branch-and-cut to improve the efficiency of the search [36,37].…”

Section: Discussionmentioning

confidence: 99%

Converting MST to TSP Path by Branch Elimination

2020

View full text Add to dashboard Cite

Travelling salesman problem (TSP) has been widely studied for the classical closed loop variant but less attention has been paid to the open loop variant. Open loop solution has property of being also a spanning tree, although not necessarily the minimum spanning tree (MST). In this paper, we present a simple branch elimination algorithm that removes the branches from MST by cutting one link and then reconnecting the resulting subtrees via selected leaf nodes. The number of iterations equals to the number of branches (b) in the MST. Typically, b << n where n is the number of nodes. With O-Mopsi and Dots datasets, the algorithm reaches gap of 1.69% and 0.61 %, respectively. The algorithm is suitable especially for educational purposes by showing the connection between MST and TSP, but it can also serve as a quick approximation for more complex metaheuristics whose efficiency relies on quality of the initial solution.

show abstract

Section: Discussionmentioning

confidence: 99%

Converting MST to TSP Path by Branch Elimination

2020

View full text Add to dashboard Cite

show abstract

“…ere is abundant literature on heuristic algorithms for optimization problems [25][26][27][28][29][30]. For example, Homsi et al [31] proposed an exact branch-and-price algorithm and a hybrid genetic search to study industrial and tramp ship routing and scheduling problems. Vidal et al [32] proposed an efficient hybrid genetic algorithm with advanced diversity control for a large class of vehicle routing problems with time windows.…”

Section: Literature Reviewmentioning

confidence: 99%

Two-Stage Solution for Meal Delivery Routing Optimization on Time-Sensitive Customer Satisfaction

Wang

Jiang

2022

Journal of Advanced Transportation

View full text Add to dashboard Cite

The online-to-offline (O2O) meal delivery mode in which takeout meals are ordered online and delivered offline is recently emerging. The fast delivery of huge meal orders for time-sensitive customers imposes great challenges on O2O meal delivery platforms. This study establishes a two-stage solution for meal delivery routing optimization with the objective of maximizing time-sensitive customer satisfaction. In the first stage, a large number of meal orders are hierarchically classified and merged into delivery bundles based on the nearest pickup location rule by applying the hierarchical agglomerative clustering (HAC) algorithm, to increase fast meal delivery efficiency. In the second stage, a genetic algorithm (GA) is applied to solve the cluster-based delivery routing optimization model to find an optimal delivery route for meal orders in each delivery bundle. The numerical simulation results verify that the two-stage routing optimization solution is effective to schedule timely meal delivery and improve customer time satisfaction. The comparison of the results indicates the superiority of the proposed two-stage solution with HAC and GA on customer satisfaction while ensuring the delivery of all orders within 60 minutes. The sensitivity analysis shows the impact of time-sensitive customer heterogeneity on meal delivery satisfaction. This research has significant managerial insights for fast delivery services of O2O meal delivery platforms.

show abstract

“…This scenario sometimes results in missing the time window because of the low-speed voyage. Homsi et al (2020) described the generation of elementary routes for tackling routing problems related to industrial and tramp ships. However, load-dependent fuel consumption, sea condition, and emission-related vital points were not considered there.…”

Section: Literature Studymentioning

confidence: 99%

Solving fuzzy dynamic ship routing and scheduling problem through new genetic algorithm

Das¹,

Roy²,

Maity

et al. 2022

Decis. Mak. Appl. Manag. Eng.

View full text Add to dashboard Cite

Main motto of ship routing and scheduling is to reduce the total transportation cost of each ship or vessel without interrupting the demand and supply. In this study, we have proposed a ship routing and scheduling model for commercial ships where, to ensure unhindered demand and supply of products at various ports in a fixed time frame, the dynamic demand and supply of each port were considered under a fuzzy environment. Additionally, simultaneous loading and unloading and a fixed load factor is used to minimize port time and reduce risks, and this aspect of our work makes it realistically inclined. We also show, in our work, speed optimization to reduce fuel consumption and carbon emission. In practice, cost parameters cannot be always determined, it fluctuates at a certain range from time to time. We have treated the imprecise cost parameters as triangular fuzzy numbers. With a view to working with the developed model, a modified genetic algorithm (MGA) with a new selection technique, namely an in-vitro-fertilization-based crossover, and a generation-dependent mutation is proposed. The proposed sustainable ship routing algorithm with dynamic demand and supply in an uncertain environment gives a novelty in the literature. Another novelty is incurred through the proposed MGA in the heuristic search algorithms. This algorithm has produced numerical results superior to those of other heuristic algorithms. We have also established the efficiency of the proposed algorithm through statistical experiments.

show abstract

Industrial and tramp ship routing problems: Closing the gap for real-scale instances

Cited by 24 publications

References 48 publications

Converting MST to TSP Path by Branch Elimination

Converting MST to TSP Path by Branch Elimination

Two-Stage Solution for Meal Delivery Routing Optimization on Time-Sensitive Customer Satisfaction

Solving fuzzy dynamic ship routing and scheduling problem through new genetic algorithm

Contact Info

Product

Resources

About