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Articles 1 - 14 of 14
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu
Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu
Research Collection School Of Computing and Information Systems
This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processed on a specific machine, defined as: R|rj,eij,STsd|Cmax. The objective is first to maximize the number of processed jobs, then minimize the maximum completion time (makespan), and finally minimize the maximum completion times of the non-bottleneck machines. A mixed-integer programming (MIP) model is proposed as a solution approach …
A Matheuristic Algorithm For The Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
A Matheuristic Algorithm For The Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
This paper studies the integration of the vehicle routing problem with cross-docking (VRPCD). The aim is to find a set of routes to deliver products from a set of suppliers to a set of customers through a cross-dock facility, such that the operational and transportation costs are minimized, without violating the vehicle capacity and time horizon constraints. A two-phase matheuristic based on column generation is proposed. The first phase focuses on generating a set of feasible candidate routes in both pickup and delivery processes by implementing an adaptive large neighborhood search algorithm. A set of destroy and repair operators are …
Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Research Collection School Of Computing and Information Systems
Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …
Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen
Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen
Research Collection School Of Computing and Information Systems
The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the Generalized OP, the Arc OP, …
Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen
Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen
Research Collection School Of Computing and Information Systems
Duplicate record, see https://ink.library.smu.edu.sg/sis_research/3271. The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the …
Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham
Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Emergency Medical Systems (EMSs) are an important component of public health-care services. Improving infrastructure for EMS and specifically the construction of base stations at the ”right” locations to reduce response times is the main focus of this paper. This is a computationally challenging task because of the: (a) exponentially large action space arising from having to consider combinations of potential base locations, which themselves can be significant; and (b) direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that …
Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein
Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Decentralized POMDP is an expressive model for multi-agent planning. Finite-state controllers (FSCs)---often used to represent policies for infinite-horizon problems---offer a compact, simple-to-execute policy representation. We exploit novel connections between optimizing decentralized FSCs and the dual linear program for MDPs. Consequently, we describe a dual mixed integer linear program (MIP) for optimizing deterministic FSCs. We exploit the Dec-POMDP structure to devise a compact MIP and formulate constraints that result in policies executable in partially-observable decentralized settings. We show analytically that the dual formulation can also be exploited within the expectation maximization (EM) framework to optimize stochastic FSCs. The resulting EM algorithm …
Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We study a real-world problem arising from the operations of a hospital service provider, which we term the master physician scheduling problem. It is a planning problem of assigning physicians’ full range of day-to-day duties (including surgery, clinics, scopes, calls, administration) to the defined time slots/shifts over a time horizon, incorporating a large number of constraints and complex physician preferences. The goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We propose mathematical programming models that represent different variants of this problem. The models were tested on a real …
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …
Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau
Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We propose and explore, in the context of benchmark problems for flowshop scheduling, a risk-based concept of robustness for optimization problems. This risk-based concept is in distinction to, and complements, the uncertainty-based concept employed in the field known as robust optimization. Implementation of our concept requires problem solution methods that sample the solution space intelligently and that produce large numbers of distinct sample points. With these solutions to hand, their robustness scores are easily obtained and heuristically robust solutions found. We find evolutionary computation to be effective for this purpose on these problems.
Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau
Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This paper is concerned with solving decentralized resource allocation and scheduling problems via auctions with negotiable agents by allowing agents to switch their bid generation strategies within the auction process, such that a better system wide performance is achieved on average as compared to the conventional walrasian auction running with agents of fixed bid generation strategy. We propose a negotiation mechanism embedded in auctioneer to solicit bidders’ change of strategies in the process of auction. Finally we benchmark our approach against conventional auctions subject to the real-time large-scale dynamic resource coordination problem to demonstrate the effectiveness of our approach.
Dynamic Allocation Of Airline Check-In Counters: A Queueing Optimisation Approach, Mahmut Parlar, Sharafali Moosa
Dynamic Allocation Of Airline Check-In Counters: A Queueing Optimisation Approach, Mahmut Parlar, Sharafali Moosa
Research Collection Lee Kong Chian School Of Business
This paper was motivated by an observation in an international airport with regard to allocation of resources for check-in counters. In an exclusive check-in counter system, each flight has a dedicated number of counters that will be open until at least a half-hour before the scheduled departure of that flight. Currently, in many of the airports around the world, the decision to open or close check-in counters is done on an ad hoc basis by human schedulers. In doing so, the schedulers are almost always forced to perform a balancing act in meeting the quality of service stipulated by the …
Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau
Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we study the multi-machine scheduling problem with earliness and tardiness penalties and sequence dependent setup times. This problem can be decomposed into two subproblems—sequencing and timetabling. Sequencing focuses on assigning each job to a fixed machine and determine the job sequence on each machine. We call such assignment a semi-schedule. Timetabling focuses on finding an executable schedule from the semi-schedule via idle-time insertion. Sequencing is strongly NP-hard in general. Although timetabling is polynomial-time solvable, it can become a computational bottleneck if the procedure is executed many times within a larger framework. This paper makes two contributions. We …
Automated Manpower Rostering: Techniques And Experience, C. M. Khoong, Hoong Chuin Lau, L. W. Chew
Automated Manpower Rostering: Techniques And Experience, C. M. Khoong, Hoong Chuin Lau, L. W. Chew
Research Collection School Of Computing and Information Systems
We present ROMAN, a comprehensive, generic manpower rostering toolkit that successfully handles a wide spectrum of work policies found in service organizations. We review the use of various techniques and methodologies in the toolkit that contribute to its robustness and efficiency, and relate experience gained in addressing manpower rostering problems in industry.