Dynamic Vehicle Scheduling for Working Service Network with Dual Demands

This study aims to develop some models to aid in making decisions on the combined fleet size and vehicle assignment in working service network where the demands include two types (minimum demands and maximum demands), and vehicles themselves can act like a facility to provide services when they are stationary at one location. This type of problem is named as the dynamic working vehicle scheduling with dual demands (DWVS-DD) and formulated as a mixed integer programming (MIP). Instead of a large integer program, the problem is decomposed into small local problems that are guided by preset control parameters. The approach for preset control parameters is given. By introducing them into the MIP formulation, the model is reformulated as a piecewise form. Further, a piecewise method by updating preset control parameters is proposed for solving the reformulated model. Numerical experiments show that the proposed method produces better solution within reasonable computing time

An analysis of price disparity: Peninsular Malaysia and Sabah

This study examines the price differences between Peninsular Malaysia and Sabah from 2004 using quantitative and qualitative methods. For quantitative research, we employ disaggregate monthly consumer price indices for nine types of goods and services. Based on the Johansen co-integration test, the results reveal that the long-run relationship only exists for transport group. The findings using Granger pair-wise causality test indicated that the prices in Peninsular Malaysia do not determined the price in Sabah. Qualitative research was further conducted via interviews with stakeholders of shipping providers, port authority, government and special interest group show that the price disparity between Peninsular Malaysia and Sabah occurred due to trade imbalance, sluggish economic activities, poor accessibility between port and retailers, insufficient infrastructure and technical facilities and political sentiment

New challenges in fleet deployment considering EU oil sanctions

Due to European Union (EU) oil sanctions, tanker shipping companies need to redeploy their tankers by moving tankers between ship routes with the consideration of flag states of tankers, but the literature lacks quantitative methods for this problem. To fill this research gap, this paper studies an integrated problem of fleet deployment, fleet repositioning, round trip completion, and speed optimization with the consideration of flag states of tankers. The problem is formulated as a nonlinear integer programming model to minimize the total cost, including the fleet repositioning cost, the mismatch cost, and the fuel cost, during the planning period while satisfying the total crude oil transportation demand of each voyage and the minimum shipping frequency. Some linearization methods are used to transform the nonlinear model to a linear one which can be directly solved by Gurobi. The average solving time required for 17 computational instances is 4.5 minutes, which validates the effectiveness of the proposed model. Sensitivity analyses, including the influences of the unit fuel price, the total crude oil transportation demand, the mismatch cost of completing a round trip by a deployed tanker, and the repositioning cost for each deployed tanker, on operations decisions, are conducted to obtain managerial insights

The Liner Shipping Fleet Repositioning Problem with Cargo Flows

Tierney K, Møller Jensen R. The Liner Shipping Fleet Repositioning Problem with Cargo Flows. In: Hu H, Shi X, Stahlbock R, Voß S, eds. Computational Logistics: Third International Conference, ICCL 2012, Shanghai, China, September 24-26, 2012. Proceedings. Lecture Notes in Computer Science. Vol 7555. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012: 1-16

Solving the Liner Shipping Fleet Repositioning Problem with Cargo Flows

Tierney K, Áskelsdóttir B, Jensen RM, Pisinger D. Solving the Liner Shipping Fleet Repositioning Problem with Cargo Flows. Transportation Science. 2015;49(3):652-674.We solve a central problem in the liner shipping industry called the liner shipping fleet repositioning problem (LSFRP). The LSFRP poses a large financial burden on liner shipping firms. During repositioning, vessels are moved between routes in a liner shipping network. Liner carriers wish to reposition vessels as cheaply as possible without disrupting cargo flows. The LSFRP is characterized by chains of interacting activities with a multicommodity flow over paths defined by the activities chosen. Despite its industrial importance, the LSFRP has received little attention in the literature. We introduce a novel mathematical model and a simulated annealing algorithm for the LSFRP with cargo flows that makes use of a carefully constructed graph; we evaluate these approaches using real-world data from our industrial collaborator. Additionally, we compare the performance of our approach against an actual repositioning scenario, one of many undertaken by our industrial collaborator in 2011. Our simulated annealing algorithm is able to increase the profit from $18.1 to$31.8 million using only a few minutes of CPU time. This shows that our algorithm could be used in a decision support system to solve the LSFRP