Ek Peng Chew

Perfect decomposition techniques in energy and environmental analysis

Abstract In a recent article, Albrecht et al. (Energy Policy 30 (2002) 727) presented a new decomposition technique based on the Shapley value and used it to study CO 2 emissions in four OECD countries. This technique makes it possible to present decomposition without residuals, a very desirable property in decomposition analysis. We show that their proposed technique and the method by Sun (Energy Economics 20 (1998) 85) are exactly the same. As there has been a great deal of interest in decomposition analysis in energy policy studies, we extend the work by Albrecht et al. (Energy Policy 30 (2002) 727) by giving a more complete and up-to-date overview of perfect decomposition techniques and their role in energy demand and related analysis.

An optimization model for storage yard management in transshipment hubs

This paper studies a yard storage allocation problem in a transshipment hub where there is a great number of loading and unloading activities. The primary challenge is to efficiently shift containers between the vessels and the storage area so that reshuffling and traffic congestion is minimized. In particular, to reduce reshuffling, a consignment strategy is used. This strategy groups unloaded containers according to their destination vessel. To reduce traffic congestion, a new workload balancing protocol is proposed. A mixed integer-programming model is then formulated to determine the minimum number of yard cranes to deploy and the location where unloaded containers should be stored. The model is solved using CPLEX. Due to the size and complexity of this model two heuristics are also developed. The first is a sequential method while the second is a column generation method. A bound is developed that allows the quality of the solution to be judged. Lastly, a numerical investigation is provided and demonstrates that the algorithms perform adequately on most cases considered.

Travel time analysis for general item location assignment in a rectangular warehouse

A travel time model with general item location assignment in a rectangular warehouse system is presented. We give the exact probability mass functions that characterise the tour of an order picker and derive the first and second moments associated with the tour. We apply the model to analysing order batching and storage allocation strategies in an order picking system. The order picking system is modelled as a queueing system with customer batching. The results are compared and validated via simulation. The effects of batching and batch size on the delay time are discussed with consideration to the picking and sorting times for each batch of orders.

A decision model for berth allocation under uncertainty

This paper studies the berth allocation problem (BAP) under uncertain arrival time or operation time of vessels. It does not only concern the proactive strategy to develop an initial schedule that incorporates a degree of anticipation of uncertainty during the schedules execution, but also studies the reactive recovery strategy which adjusts the initial schedule to handle realistic scenarios with minimum penalty cost of deviating from the initial schedule. A two-stage decision model is developed for the BAP under uncertainties. Moreover, a meta-heuristic approach is proposed for solving the above problem in large-scale realistic environments. Numerical experiments are conducted to validate the effectiveness and efficiency of the proposed method.

A yard storage strategy for minimizing traffic congestion in a marine container transshipment hub

This paper studies a storage yard management problem in a transshipment hub where the loading and unloading activities are both heavy and concentrated. In order to reduce the number of reshuffles, which helps to reduce the vessel turnaround time, the port operator uses the consignment strategy to group export and transshipment containers according to their destination vessel. To reduce the potential traffic congestion of prime movers, a high–low workload balancing protocol is used. A mixed integer programming model is formulated to determine the storage locations of incoming containers, the number of incoming containers and the smallest number of yard cranes to deploy in each shift. An iterative improvement method is developed to solve the problem, in which a tabu search based heuristic algorithm is used to generate an initial yard template, and then the generated yard template is improved by an improvement algorithm iteratively until an optimal or a satisfactory solution is obtained. Experiment results show that the proposed method can generate excellent results within a reasonable time, even for the extreme cases.

Multi-objective simulation-based evolutionary algorithm for an aircraft spare parts allocation problem

Simulation optimization has received considerable attention from both simulation researchers and practitioners. In this study, we develop a solution framework which integrates multi-objective evolutionary algorithm (MOEA) with multi-objective computing budget allocation (MOCBA) method for the multi-objective simulation optimization problem. We apply it on a multi-objective aircraft spare parts allocation problem to find a set of non-dominated solutions. The problem has three features: huge search space, multi-objective, and high variability. To address these difficulties, the solution framework employs simulation to estimate the performance, MOEA to search for the more promising designs, and MOCBA algorithm to identify the non-dominated designs and efficiently allocate the simulation budget. Some computational experiments are carried out to test the effectiveness and performance of the proposed solution framework.

Finding the non-dominated Pareto set for multi-objective simulation models

This article considers a multi-objective Ranking and Selection (R+S) problem, where the system designs are evaluated in terms of more than one performance measure. The concept of Pareto optimality is incorporated into the R+S scheme, and attempts are made to find all of the non-dominated designs rather than a single “best” one. In addition to a performance index to measure how non-dominated a design is, two types of errors are defined to measure the probabilities that designs in the true Pareto/non-Pareto sets are dominated/non-dominated based on observed performance. Asymptotic allocation rules are derived for simulation replications based on a Lagrangian relaxation method, under the assumption that an arbitrarily large simulation budget is available. Finally, a simple sequential procedure is proposed to allocate the simulation replications based on the asymptotic allocation rules. Computational results show that the proposed solution framework is efficient when compared to several other algorithms in terms of its capability of identifying the Pareto set.

Simultaneous optimization of horizontal and vertical alignments for highways

This paper presents the formulation of a three-dimensional highway alignment optimization model. The coordinates of the highway is parametrized by using a three-dimensional cubic spline polynomial interpolation. The solution is obtained by locating the optimal horizontal and vertical alignments simultaneously while subject to a wide range of possible constraints. These constraints may be bounds on the slope or curvature, as well as avoidance of inaccessible region. It is an extension from a previous research work where optimal vertical highway alignment was determined for a preselected horizontal alignment. Two numerical examples based upon the actual ground conditions in Singapore are presented to illustrate the applicability of the proposed model. Some computational details such as scaling and selection of initial variables which affect the rate of convergence are also briefly discussed.

Discrete and continuous models for computation of optimal vertical highway alignment

This paper describes a dynamic programming model and a state parametrization model formulated to solve two-dimensional highway location problems. A numerical example is presented to compare the solutions obtained using the two models. Features of the two approaches, with respect to their applicability in solving three-dimensional highway location problems in particular, are highlighted. This study forms the basis of a three-dimensional model that computes optimal horizontal and vertical alignments simultaneously.

A container yard storage strategy for improving land utilization and operation efficiency in a transshipment hub port

This paper studies the storage yard management problem in a busy transshipment hub, where intense loading and unloading activities have to be considered at the same time. The need to handle huge volumes of container traffic and the scarcity of land in the container port area pose serious challenges for the port operator to provide efficient services. A consignment strategy with a static yard template has been used to reduce the level of reshuffles in the yard, but it sacrifices on land utilization because of exclusive storage space reservation. Two space-sharing approaches are proposed to improve on the land utilization through dynamic reservation of storage space for different vessels during different shifts. Meanwhile, workload assignment among reserved spaces will also satisfy the high-low workload balancing protocol to reduce traffic congestion in the yard. A framework which integrates space reservation and workload assignment is proposed. Experimental results show that the framework is able to provide solutions for containers handling within much less storage space, while guarantee the least yard crane deployment.