A joint optimization model for liner container cargo assignment problem using state-augmented shipping network framework

This paper proposes a state-augmented shipping (SAS) network framework to integrate various activities in liner container shipping chain, including container loading/unloading, transshipment, dwelling at visited ports, in-transit waiting and in-sea transport process. Based on the SAS network framework, we develop a chance-constrained optimization model for a joint cargo assignment problem. The model attempts to maximize the carrier’s profit by simultaneously determining optimal ship fleet capacity setting, ship route schedules and cargo allocation scheme. With a few disparities from previous studies, we take into account two differentiated container demands: deterministic contracted basis demand received from large manufacturers and uncertain spot demand collected from the spot market. The economies of scale of ship size are incorporated to examine the scaling effect of ship capacity setting in the cargo assignment problem. Meanwhile, the schedule coordination strategy is introduced to measure the in-transit waiting time and resultant storage cost. Through two numerical studies, it is demonstrated that the proposed chance-constrained joint optimization model can characterize the impact of carrier’s risk preference on decisions of the container cargo assignment. Moreover, considering the scaling effect of large ships can alleviate the concern of cargo overload rejection and consequently help carriers make more promising ship deployment schemes.     

Optimal shipment decisions for an airfreight forwarder: Formulation and solution methods

We study the freight forwarder’s shipment planning problem in an airfreight forwarding network where a set of cargo shipments have to be transported to given destinations. We provide mixed integer programming formulations that use piecewise-linear cargo rates and account for volume and weight constraints, flight departure/arrival times, as well as shipment-ready times.After exploring the solution of such models using CPLEX, we devise two solution methodologies to handle large problem sizes. The first is based on Lagrangian relaxation, where the problems decompose into a set of knapsack problems and a set of network flow problems. The second is a local branching heuristic that combines branching ideas and local search. The two approaches show promising results in providing good quality heuristic solutions within reasonable computational times, for difficult and large shipment consolidation problems.     

A Lagrangian relaxation based heuristic for the consolidation problem of airfreight forwarders

International air cargo is an operation-intensive industry, involving complex procedures and many players. As an important player, airfreight forwarders need to consolidate the collected goods skillfully in order to satisfy the requirements of the shippers and, at the same time minimize the expense charged by the airlines. However, the air cargo rate structure is very complicated, making the consolidation a difficult mixed-integer programming problem for the airfreight forwarder. In this paper, the consolidation problem is first transformed into a well-known set covering problem by treating a feasible consolidated shipment as a set. Lagrangian Relaxation is used as the backbone to develop a recursive heuristic algorithm. Based on the numerical experiment, the heuristic algorithm generates solutions very close to optimality. In particular, a sensitivity analysis is performed with respect to the degree of concavity. The results suggest that the solution algorithm can be used as a core module of the decision support system for air cargo consolidation.     

A tailored branch-and-price approach for a joint tramp ship routing and bunkering problem

This paper deals with a practical tramp ship routing problem while taking into account different bunker prices at different ports, which is called the joint tramp ship routing and bunkering (JSRB) problem. Given a set of cargoes to be transported and a set of ports with different bunker prices, the proposed problem determines how to route ships to carry the cargoes and the amount of bunker to purchase at each port, in order to maximize the total profit. After building an integer linear programming model for the JSRB problem, we propose a tailored branch-and-price (B&P) solution approach. The B&P approach incorporates an efficient method for obtaining the optimal bunkering policy and a novel dominance rule for detecting inefficient routing options. The B&P approach is tested with randomly generated large-scale instances derived from real-world planning problems. All of the instances can be solved efficiently. Moreover, the proposed approach for the JSRB problem outperforms the conventional sequential planning approach and can incorporate the prediction of future cargo demand to avoid making myopic decisions.     

The structure of the solution set to network optimisation problems

This paper argues that both heuristic and non-heuristic algorithms for the road network optimisation problem would benefit from a greater understanding of the structure of the set of feasible solutions to such problems. In order to provide this, a comparative study of a number of spatial combinatorial problems was undertaken. The results show that the road network optimisation problem is rich in good sub-optimal solutions. The implications of this finding for the development of optimising and heuristic algorithms are discussed, and some suggestions made as to where future research on network optimisation problems could most fruitfully be directed.     

Liner shipping network design with emission control areas: A genetic algorithm-based approach

To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO₂ and SO_x) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances.     

Cluster analysis of the competitiveness of container ports in Brazil

The container cargo proportion of total maritime transport increased from 3% in 1980 to 16% in 2011. The largest Brazilian port, the port of Santos, is the 42nd largest container port in the world. However, Santos’ performance indicators are much lower than those of the world’s largest ports, so comparisons with them are difficult. This article focuses on the Brazilian container terminals that handled containers in 2009 and compares port competitiveness. This study classified seventeen Brazilian container terminals into three distinct groups based on the following competitiveness criteria: number of containers handled, berth length, number of berths, terminal tariffs (in US$), berth depth, rate of medium consignment (in containers/ship), medium board (containers/hour), average waiting time for mooring (in hours/ship), and average waiting time for load or unload cargo (in hours/ship). This classification used a hierarchical cluster analysis. The classification shows that the terminal of Tecon in the port of Santos has the best performance of all, while small terminals (<150,000 container units) are the worst performing terminals in Brazil.     

Power unit ‐ Cargo space link in inland waterway navigation

This paper deals with transportation technology regarding links between power unit or motor ship and ship cargo space. These links can be divided into two groups: rigid and flexible. Rigid link, established between power unit and cargo space, is dominant in maritime and road transport (sea ships and trucks), and occasionally in transport on inland waterways (self‐propelled barges). Flexible link is used in railroad transport (between the locomotive and railroad units), partially in road transport (systems with trailers and semitrailers), and in inland waterway transport (push‐towing, pulling systems and combinations of these systems). The main goal of this research is determination of possible link types and organization of fleet for transport on inland waterways in case of flexible link.     

Testing and evaluation of a multi-commodity multi-modal network flow model for disaster relief management

The results of the testing of an optimization model in disaster relief management are presented. The problem is a large-scale multi-commodity, multi-modal network flow problem with time windows. Due to the nature of this problem, the size of the optimization model grows extremely rapidly as the number of modes and/or commodities increase. The formulation is based on the concept of a time-space network. Two heuristic algorithms are developed. One exploits an inherent network structure of the problem with a set of side constraints and the other is an interactive fix-and-run heuristic. The findings of the model-testing and a wide range of sensitivity analyses using an artificially generated data set are presented. Both solution procedures prove to be efficient and effective in providing close to optimal solutions.     

A lamda-optimal based heuristic for the berth scheduling problem

Berth scheduling aims to optimally schedule vessels to berthing areas along a quay and is a complex optimization problem. In this paper we propose a lamda-optimal based heuristic as a resolution approach for the discrete space berth scheduling problem. The proposed heuristic can also be applied to validate optimality, in the case where other (meta)heuristics are applied as resolution approaches. A second internal Genetic Algorithms based heuristic is also proposed to reduce the computational time required for medium to large scale instances. Numerical experiments performed show that the proposed heuristic is adequate to produce near-optimal results within acceptable computational times.     

Developing a comprehensive programme for improving shipboard energy efficiency

This article identifies a set of fuel saving strategies designed to meet the needs of vessel owners and operators, and describes how the strategies can be combined into a comprehensive programme. The strategies are developed from over sixty potential fuel saving measures grouped on the basis of commonness of purpose and interdependency. These criteria reflect the finding that implementing certain strategies is a prerequisite to the success of other strategies, and the success of some strategies generates a need to implement other strategies. Operational strategies identified include: developing crew motivation for active participation in energy efficiency improvement programmes; altering ship speeds; reducing auxiliary load on main propulsion plant; improved matching of ship capacities and cargo volume; reducing miles traveled; and maximizing use of electronic navigation and communications aids. Physical plant modification strategies identified include: optimizing for reduced ship speeds; fuel switching, blending and modifying; hydrodynamic improvements to the hull and propeller; and improving thrust.     

重庆市内河船舶污染物排放现状及LNG动力船舶推广效益分析

重庆地处长江上游经济带核心地区,水运发达,随着客货运量逐年增加,通行的内河船舶尾气排放严重影响港口及航道附近大气环境,已成为重庆大气污染的主要来源之一,颗粒物、NO_x的排放分别占重庆市总排放的4.3%、21.9%,SO_2占年排放的7.4%(14.8%。在大气环境问题日益严峻的情况下,LNG动力船舶因其可明显降低排气污染物,越发受到社会关注,对重庆市单LNG动力示范船舶尾气排放进行实测,对比柴油动力船舶,颗粒物、NO_x、SO_2减排显著,减排率分别达99.94%、72.69%、100%。因此,LNG动力船舶的推广表现出明显的环境效益,同时,综合分析了当前LNG动力船舶推广存在问题及困难。     

The two-echelon time-constrained vehicle routing problem in linehaul-delivery systems

Most of the studies address issues relating to the delivery from satellites to customers, which is throughout the end part of the linehaul-delivery system. Differing from the long-term strategic problems including the two-echelon vehicle routing problem (2E-VRP), the two-echelon location routing problem (2E-LRP) and the truck and trailer routing problem (TTRP) which make location decisions in depots or satellites, the paper introduces a short-term tactical problem named the two-echelon time-constrained vehicle routing problem in linehaul-delivery systems (2E-TVRP) that does not involve location decisions. The linehaul level and the delivery level are linked through city distribution centers (CDCs) located on the outskirts of cities. The 2E-TVRP has inter-CDC linehaul on the first level and urban delivery from CDCs to satellites on the second level. Vehicle routes on different levels are interacted by time constraints. A mixed integer nonlinear programming model for the 2E-TVRP is put forward, and a mixed integer linear programming model is used as the benchmark model. The Clarke and Wright savings heuristic algorithm (CW) improved by a local search phase is adopted. The 2E-TVRP formulations and the heuristic algorithm are tested by using 140 randomly-generated instances with up to 10 CDCs and 500 satellites. The computational results indicate that the heuristic can effectively solve various instances of the 2E-TVRP.     

Solution methods for the taxi pooling problem

In Taiwan, taxi pooling is currently performed by some taxi companies using a trial-and-error experience-based method, which is neither effective nor efficient. There is, however, little in the literature on effective models and solution methods for solving the taxi pooling problem. Thus, in this study we employ network flow techniques and a mathematical programming method to develop a taxi pooling solution method. This method is composed of three models. First, a fleet routing/scheduling model is constructed to produce fleet/passenger routes and schedules. A solution algorithm, based on Lagrangian relaxation, a sub-gradient method and a heuristic to find the upper bound of the solution, is proposed to solve the fleet routing/scheduling model. Then, two single taxi-passenger matching models are constructed with the goals of decreasing number of passenger transfers and matching all passengers and taxis. These two taxi-passenger matching models are directly solved using a mathematical programming solver. For comparison with the solution method, we also develop another heuristic by modifying a heuristic recently proposed for solving a one-to-many taxi pooling problem. The performance of the solution method and the additional heuristic are evaluated by carrying out a case study using real data and suitable assumptions. The test results show that these two solution methods could be useful in practice.     

The impact of scale on energy intensity in freight transportation

This paper analyzes energy intensities of ships, diesel–fuelled railways, trucks, and aircraft, using publicly available data. The analysis suggests that differences in operation, not technology, explain most of the variation in energy intensity within and across modes. Among the operational characteristics, most important is the amount of cargo weight transported per vehicle and therefore the scale of the respective transportation system. It is found that each mode has a characteristic envelope in an average energy intensity versus average cargo weight diagram, and estimates of the elasticities of energy intensity with respect to load size are made.     

Can ports increase traffic while reducing inputs? Technical efficiency of Spanish Port Authorities using a directional distance function approach

The focus of this paper is on the productive efficiency of ports. We estimate a directional technology distance function using parametric techniques to analyze the production technology and technical efficiency of a set of Spanish Port Authorities observed over the period 1993–2012. Technical inefficiency is conceived as the ability of ports to simultaneously expand a given output and contract variable inputs while maintaining quasi-fixed inputs and other outputs constant. Thus, for containerized cargo we address the following question: Given the amount of quasi-fixed inputs used by the firm and given the volume of the other outputs (liquids, solids, non-containerized cargo and passenger traffic), could ports increase their containerized merchandise while simultaneously reducing their variable inputs? Similar questions are asked for solid bulk and non-containerized general cargo. Our results show evidence of technical inefficiency among the ports in our sample. In particular, if the ports operated efficiently, we find that containerized cargo could be expanded by an average of over 6.4%, with an equivalent reduction in variable inputs. Solid bulk cargo and general non-containerized cargo could be increased by 4.1% and 6.1% respectively, with corresponding reductions in variable inputs. An implication of our results is that there is ample scope for specialization on the part of ports with no increase in infrastructure costs. Given that large investments in infrastructure have been made in Spanish port over the last decade, this opens the possibility of moving towards a management model based on taking advantage of existing capacity rather than new investments.     

A discrete-convex programming approach to the simultaneous optimization of land use and transportation

Three design problems are discussed in this article. First, it is shown that the network design problem with congestion reduces to an all-or nothing traffic assignment problem under some assumptions on the congestion function and the investment cost function. Second, the land use design problem is formulated as an extension of the Koopmans-Beckmann problem and a heuristic is proposed to solve this problem. Third, it is shown that the seemingly more complex problem of designing jointly a land-use plan and a transportation network reduces to a pure land-use design problem. All that is needed to solve the joint optimization problem is a shortest path algorithm and a heuristic to solve the land use design problem. Computational experience is reported for each algorithm.     

A distributed origin–destination demand estimation approach for real-time traffic network management

Abstract

This paper describes a distributed recursive heuristic approach for the origin–destination demand estimation problem for real-time traffic network management applications. The distributed nature of the heuristic enables its parallelization and hence reduces significantly its processing time. Furthermore, the heuristic reduces dependency on historical data that are typically used to map the observed link flows to their corresponding origin–destination pairs. In addition, the heuristic allows the incorporation of any available partial information on the demand distribution in the study area to improve the overall estimation accuracy. The heuristic is implemented following a hierarchal multi-threading mechanism. Dividing the study area into a set of subareas, the demand of every two adjacent subareas is merged in a separate thread. The merging operations continue until the demand for the entire study area is estimated. Experiments are conducted to examine the performance of the heuristic using hypothetical and real networks. The obtained results illustrate that the heuristic can achieve reasonable demand estimation accuracy while maintaining superiority in terms of processing time.     

A proof of the relationship between optimal vehicle size,haulage length and the structure of distance-transport costs

This paper deals with two interrelated questions, namely the optimum size of a vehicle or vessel, and the structure of transport costs with respect to haulage distance. The relationship between these two questions has not been coherently dealt with previously in the literature, and the heuristic attempts at doing so have lead to both theoretical and empirical anomalies. This paper adopts an inventory optimisation approach in order to show that both of these questions can be treated in a unified manner and this allows us to show, first, that under very general conditions the optimum size of a ship increases with the haulage distance and haulage weight, and second, that the observed structure of transport costs with respect to the haulage distance and quantity is itself a result of this optimisation problem.     

In Search of the Link between Ship Size and Operations

Abstract

Since 1990s the liner shipping industry has faced a period of restructuring and consolidation, and been confronted with a continuing increase in container vessel scale. The impact of these changes is noticeable in trade patterns, cargo handling methods and shipping routes, in short ‘operations’. After listing factors influencing size, growth in container ship size is explained by economies of scale in deploying larger vessels. In order to quantify economies of scale, this paper uses the liner service cash flow model. A novelty in the model is the inclusion of +6000-20-foot Equivalent Unit (TEU) vessels and the distinction in costs between single and twin propeller units on ships. The results illustrate that scale economies have been – and will continue to be – the driving force behind the deployment of larger container vessels. The paper then assesses the link between ship size and operations, given current discussions about the increase in container vessel scale. It is found that (a) ship size and operations are linked; (b) optimal ship size depends on transport segment (deep-sea vs. short-sea shipping, SSS), terminal type (transhipment terminals vs. other terminals), trade lane (East-West vs. North-South trades) and technology; and (c) a ship optimal for one trade can be suboptimal for another.