Lixin Miao

A hybrid approach for the vehicle routing problem with three-dimensional loading constraints

This paper addresses a recently practical combinatorial problem named Three-Dimensional Loading Capacitated Vehicle Routing Problem, which combines three-dimensional loading problem and vehicle routing problem in distribution logistics. The problem requires a combinatorial optimization of a feasible loading and successive routing of vehicles to satisfy customer demands, where all vehicles must start and finish at a central depot. The goal of this combinatorial problem is to minimize the total transportation cost while serving customers. Despite its clearly practical significance in the real world distribution management, for its high combinatorial complexity, published papers on this problem in literature are very limited. We present a hybrid approach which combines Honey Bee Mating Optimization and six loading heuristics, one for vehicle routing and the other for three-dimensional loading, to solve the integrated problem. We computationally evaluate this hybrid approach on all publicly available test instances, and obtain new best solutions for several scenarios.

A local search method for periodic inventory routing problem

Inventory routing problem considers inventory allocation and routing problems simultaneously, in which the replenishment policies and routing arrangement are determined by the supplier under the vendor managed inventory mode. What we consider here is a periodic inventory routing problem that once the delivery time, quantity and routing are determined, they will remain the same in the following periods. The problem is modeled concisely, and then it is decomposed into two subproblems, inventory problem and vehicle routing problem. The inventory problem is solved by proposing a local search method, which is achieved by four operators on delivery quantity and retailers demand. Insertion operator aims to insert a new replenishment point of a retailer while removal operator is to remove a replenishment point. Besides, addition operator is adopted as an assistant tool, and crossover operator is proposed for some special cases. We also propose a tabu search method to solve the routing problem. Finally, the computational results show that the method is efficient and stable.

Controlling GHG emissions from the transportation sector through an ETS: institutional arrangements in Shenzhen, China

Many different approaches are needed to achieve reductions in GHG emissions from the transportation sector. Carbon emissions trading schemes (ETSs) are widely used in industry and are effective in reducing the overall social cost of emissions abatement. This article reports the development of a downstream ETS for the transportation sector and its application in Shenzhen, China. The ETS was devised as a mandatory cap-and-trade scheme and, as a first step, was applied to public transportation. An integrated cap was set on the total emissions from buses and taxis: an absolute cap for existing vehicles and a relative increment for new entrants. Allowances were allocated by grandfathering or benchmarking and a ‘reverse mechanism’ was established to encourage the transformation of urban transportation to a low-carbon system. Online fuel consumption monitoring was used to quantify the emissions from vehicles, and the operators were required to surrender enough allowances or credits to account for their verified annual emissions. The mechanisms for allowance trading and carbon offsets provided sufficient flexibility to make emissions abatement and the use of new-energy vehicles and environmentally friendly travel within Shenzhens urban transportation system economically attractive. Policy relevance The transportation sector is becoming a major contributor to the growth in Chinas GHG emissions. Achieving large reductions in GHG emissions from the transportation sector is a great challenge and requires both technology and policy innovation. The tradable carbon permit is a popular concept in mitigating climate change, but the introduction of a cap-and-trade ETS into the transportation sector is a relatively innovative concept. Shenzhen has launched the first cap-and-trade ETS in a developing country and is currently exploring ways to mitigate carbon emissions by a downstream cap-and-trade ETS for the transportation sector. This article considers the main institutional arrangements and regulatory framework of Shenzhens transportation carbon ETS. It not only refreshes the theoretical analysis and practical application of downstream cap-and-trade carbon emissions trading in urban transportation, but also provides developing countries with a cost-effective instrument to mitigate their rapid growth in traffic carbon emissions during urbanization.

A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem

This paper considers the mobile facility routing and scheduling problem with stochastic demand (MFRSPSD). The MFRSPSD simultaneously determines the route and schedule of a fleet of mobile facilities which serve customers with uncertain demand to minimize the total cost generated during the planning horizon. The problem is formulated as a two-stage stochastic programming model, in which the first stage decision deals with the temporal and spatial movement of MFs and the second stage handles how MFs serve customer demands. An algorithm based on the multicut version of the L-shaped method is proposed in which several lower bound inequalities are developed and incorporated into the master program. The computational results show that the algorithm yields a tighter lower bound and converges faster to the optimal solution. The result of a sensitivity analysis further indicates that in dealing with stochastic demand the two-stage stochastic programming approach has a distinctive advantage over the model considering only the average demand in terms of cost reduction.

Conservative allocation models for outbound containers in container terminals

This paper examines location assignment for outbound containers in container terminals. It is an extension to the previous modeling work of Kim et al. (2000) and Zhang et al. (2010). The previous model was an “optimistic” handling way and gave a moderate punishment for placing a lighter container onto the top of a stack already loaded with heavier containers. Considering that the original model neglected the stack height and the state-changing magnitude information when interpreting the punishment parameter and hid too much information about the specific configurations for a given stack representation, we propose two new “conservative” allocation models in this paper. One considers the stack height and the state-changing magnitude information by reinterpreting the punishment parameter and the other further considers the specific configurations for a given stack representation. Solution qualities for the “optimistic” and the two “conservative” allocation models are compared on two performance indicators. The numerical experiments indicate that both the first and second “conservative” allocation models outperform the original model in terms of the two performance indicators. In addition, to overcome computational difficulties encountered by the dynamic programming algorithm for large-scale problems, an approximate dynamic programming algorithm is presented as well.

Optimal storage rack design for a multi-deep compact AS/RS considering the acceleration/deceleration of the storage and retrieval machine

This paper explores the optimal storage rack design for a multi-deep compact Automated Storage and Retrieval System (AS/RS) considering the acceleration and deceleration of storage and retrieval (S/R) machine. The expected travel time under the single-command cycle and dual-command cycle for a random storage strategy is derived. Based on the travel time, the general models we propose calculate the optimal ratio between three dimensions that minimises the travel time under different speed profile scenarios. From the result, it is proven that the optimal storage rack design model in the constant speed situation can be treated as a special case of the model considering the acceleration and deceleration of S/R machine. Finally, this study investigates the effect of speed profile of S/R machine and fixing dimensions by various numerical experiments.

Advanced Stochastic Modeling of Railway Track Irregularities

As an important interference source of railway vibration, track irregularity is studied in this paper. It is presented that irregularities in the vertical profile and alignment can be modeled as a Gaussian random process. The power spectral density (PSD) of the irregularity is calculated and discussed. By analyzing the model, level-crossing properties as well as peak statistics are studied and compared with the observed data.

A two-stage robust optimization approach for the mobile facility fleet sizing and routing problem under uncertainty

Abstract We propose a two-stage robust optimization model for the mobile facility fleet sizing and routing problem with demand uncertainty. A two-level cutting plane based method is developed, which includes an algorithm to generate problem-specific lower bound inequalities in the outer level, and a hybrid algorithm in the inner level that combines heuristic and exact methods to solve the recourse problem. Numerical tests show that the design and operation from the proposed method outperforms other solution approaches. The efficiency of the proposed solution algorithm in identifying the optimal solution is quantified and the robustness of the proposed model is demonstrated for varying degrees of uncertainty in demand.

Location assignment for outbound containers with adjusted weight proportion

This paper studies the location assignment for arriving outbound containers during container-receiving stage. For the problem, the literature assumed that the proportion of the remaining containers on a weight group keeps unchanged throughout the container-receiving process. This assumption is inconsistent with the practice that it should be constantly adjusted according to the containers that have already been received. We therefore propose two other handling ways in this paper, leading to two new dynamic programming models. These two models are compared with the existent model on small-scale instances. For large-scale instances, a two-stage heuristic is proposed. In the first stage, a neighborhood searching heuristic is developed to generate the priority sequence of stacking patterns for each weight group of containers; in the second stage, a rollout-based heuristic is proposed to improve the incumbent solution by simulating more stack alternatives for each arriving container. The numerical experiments show that the model with adjusted weight proportion can significantly reduce state size and improve stacking quality, and that the proposed two-stage heuristic is effective and efficient for large-scale instances.

Interprovincial allocation of China's national carbon emission allowance: an uncertainty analysis based on Monte-Carlo simulations

Trade-offs between economic development and carbon emission reductions, as well as their uncertainties, are great challenges for climate change negotiations. This article focuses on the equality of Chinas national carbon allowance allocations for provincial economic development while taking into account the uncertainties in provincial economic output and business-as-usual carbon emission. The allocation equality assessment under an uncertainty model was developed based on the Gini coefficient of accumulated carbon emission per unit of gross domestic product (GDP) and Monte Carlo simulations. It was used to compare the equity and related provincial carbon abatement burdens between the grandfathering allocations under an absolute cap and the output-based benchmarking allocations under a relative cap. The results showed that the volatilities of national carbon abatement and accumulated carbon emission per unit of GDP were more stable under the relative cap. The benchmarking mechanism resulted in a more equitable allowance allocations for provincial economic development and mitigated shocks in provincial output volatility to the equity of national overall allowance allocations. This mechanism was expected to produce a more evenly distributed carbon abatement burden-sharing across provinces, and to reduce the uncertainties of provincial carbon abatements. The benchmarking mechanism is thus proposed as an appropriate choice for Chinas current equitable provincial carbon allowance allocations. Policy relevance The trade-off between economic development and carbon emission reduction is the most controversial issue in climate change negotiations. The uncertainties in economic outputs and carbon emission also pose great challenges. With the obvious imbalance and uncertainty in provincial developments, the equitable allocation of carbon allowances among provinces is the key for China to develop a national carbon emission trading scheme. The comparison of allocation mechanisms under uncertainty provides more practical suggestions for policy making in China. Benchmarking results in more equitable allowance allocation and yields more even and stable abatement burden-sharing across provinces. It narrows the gaps in economic development emissions rights between developed and less developed provinces, and mitigates the shocks of provincial outputs and business-as-usual emissions to the overall allocation equity and provincial carbon abatement burdens. This benchmarking is suggested as a reasonable choice for Chinas provincial carbon allowance allocation method.