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Book part
Publication date: 15 April 2020

Yu-Wei Hsieh and Matthew Shum

The authors propose an Markov Chain Monte Carlo (MCMC) method for estimating a class of linear sum assignment problems (LSAP; the discrete case of the optimal transport problems)…

Abstract

The authors propose an Markov Chain Monte Carlo (MCMC) method for estimating a class of linear sum assignment problems (LSAP; the discrete case of the optimal transport problems). Prominent examples include multi-item auctions and mergers in industrial organizations. This contribution is to decompose the joint likelihood of the allocation and prices by exploiting the primal and dual linear programming formulation of the underlying LSAP. Our decomposition, coupled with the data augmentation technique, leads to an MCMC sampler without a repeated model-solving phase.

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Book part
Publication date: 15 April 2020

Abstract

Details

Essays in Honor of Cheng Hsiao
Type: Book
ISBN: 978-1-78973-958-9

Article
Publication date: 23 January 2024

Dominic Loske, Tiziana Modica, Matthias Klumpp and Roberto Montemanni

Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance…

Abstract

Purpose

Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations.

Design/methodology/approach

An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account.

Findings

The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics.

Originality/value

This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Content available
Book part
Publication date: 15 April 2020

Abstract

Details

Essays in Honor of Cheng Hsiao
Type: Book
ISBN: 978-1-78973-958-9

Abstract

Details

Mathematical and Economic Theory of Road Pricing
Type: Book
ISBN: 978-0-08-045671-3

Article
Publication date: 5 March 2021

Ramazan Kursat Cecen

The purpose of this paper is to provide feasible and fast solutions for the multi-objective airport gate assignment problem (AGAP) considering both passenger-oriented and…

Abstract

Purpose

The purpose of this paper is to provide feasible and fast solutions for the multi-objective airport gate assignment problem (AGAP) considering both passenger-oriented and airline-oriented objectives, which is the total walking distance from gate to baggage carousels (TWD) and the total aircraft fuel consumption during taxi operations (TFC). In addition, obtaining feasible and near-optimal solutions in a short time reduces the gate planning time to be spent by air traffic controllers.

Design/methodology/approach

The mixed integer linear programming (MILP) approach is implemented to solve the multi-objective AGAP. The weighted sum approach technique was applied in the model to obtain non-dominated solutions. Because of the complexity of the problem, the simulated annealing (SA) algorithm was used for the proposed model. The results were compared with baseline results, which were obtained from the algorithm using the fastest gate assignment and baggage carousel combinations without any conflict taking place at the gate assignments.

Findings

The proposed model noticeably decreased both the TWD and TFC. The improvement of the TWD and TFC changed from 22.8% to 46.9% and from 4.7% to 7.1%, respectively, according to the priorities of the objectives. Additionally, the average number of non-dominated solutions was calculated as 6.94, which presents many feasible solutions for air traffic controllers to manage ground traffic while taking the airline and passenger objectives into consideration.

Practical implications

The proposed MILP model includes the objectives of different stakeholders: air traffic controllers, passengers and airlines. In addition, the proposed model can provide feasible gate and baggage carousel assignments together in a short time. Therefore, the model creates a flexibility for air traffic controllers to re-arrange assignments if any unexpected situations take place.

Originality/value

The proposed MILP model combines the TWD and TFC together for the AGAP problem using the SA. Moreover, the proposed model integrates passenger-oriented and airline-oriented objectives together and reveals the relationships between the objectives in only a short time.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 2
Type: Research Article
ISSN: 1748-8842

Keywords

Content available
Article
Publication date: 14 May 2020

Matthew D. Ferguson, Raymond Hill and Brian Lunday

This study aims to compare linear programming and stable marriage approaches to the personnel assignment problem under conditions of uncertainty. Robust solutions should exhibit…

Abstract

Purpose

This study aims to compare linear programming and stable marriage approaches to the personnel assignment problem under conditions of uncertainty. Robust solutions should exhibit reduced variability of solutions in the presence of one or more additional constraints or problem perturbations added to some baseline problems.

Design/methodology/approach

Several variations of each approach are compared with respect to solution speed, solution quality as measured by officer-to-assignment preferences and solution robustness as measured by the number of assignment changes required after inducing a set of representative perturbations or constraints to an assignment instance. These side constraints represent the realistic assignment categorical priorities and limitations encountered by army assignment managers who solve this problem semiannually, and thus the synthetic instances considered herein emulate typical problem instances.

Findings

The results provide insight regarding the trade-offs between traditional optimization and heuristic-based solution approaches.

Originality/value

The results indicate the viability of using the stable marriage algorithm for talent management via the talent marketplace currently used by both the U.S. Army and U.S. Air Force for personnel assignments.

Details

Journal of Defense Analytics and Logistics, vol. 4 no. 1
Type: Research Article
ISSN: 2399-6439

Keywords

Book part
Publication date: 13 May 2017

Yang Tang, Thomas D. Cook, Yasemin Kisbu-Sakarya, Heinrich Hock and Hanley Chiang

Relative to the randomized controlled trial (RCT), the basic regression discontinuity (RD) design suffers from lower statistical power and lesser ability to generalize causal…

Abstract

Relative to the randomized controlled trial (RCT), the basic regression discontinuity (RD) design suffers from lower statistical power and lesser ability to generalize causal estimates away from the treatment eligibility cutoff. This chapter seeks to mitigate these limitations by adding an untreated outcome comparison function that is measured along all or most of the assignment variable. When added to the usual treated and untreated outcomes observed in the basic RD, a comparative RD (CRD) design results. One version of CRD adds a pretest measure of the study outcome (CRD-Pre); another adds posttest outcomes from a nonequivalent comparison group (CRD-CG). We describe how these designs can be used to identify unbiased causal effects away from the cutoff under the assumption that a common, stable functional form describes how untreated outcomes vary with the assignment variable, both in the basic RD and in the added outcomes data (pretests or a comparison group’s posttest). We then create the two CRD designs using data from the National Head Start Impact Study, a large-scale RCT. For both designs, we find that all untreated outcome functions are parallel, which lends support to CRD’s identifying assumptions. Our results also indicate that CRD-Pre and CRD-CG both yield impact estimates at the cutoff that have a similarly small bias as, but are more precise than, the basic RD’s impact estimates. In addition, both CRD designs produce estimates of impacts away from the cutoff that have relatively little bias compared to estimates of the same parameter from the RCT design. This common finding appears to be driven by two different mechanisms. In this instance of CRD-CG, potential untreated outcomes were likely independent of the assignment variable from the start. This was not the case with CRD-Pre. However, fitting a model using the observed pretests and untreated posttests to account for the initial dependence generated an accurate prediction of the missing counterfactual. The result was an unbiased causal estimate away from the cutoff, conditional on this successful prediction of the untreated outcomes of the treated.

Book part
Publication date: 3 February 2015

Bartosz Sawik

This chapter presents two multicriteria optimization models with bi and triple objectives solved with weighted-sum approach. Solved problems are allocation of personnel in a…

Abstract

This chapter presents two multicriteria optimization models with bi and triple objectives solved with weighted-sum approach. Solved problems are allocation of personnel in a health care institution. To deal with these problems, mixed integer programming formulation has been applied. Results have shown the impact of problem parameter change for importance of the different objectives. Presented problems have been solved using AMPL programming language with solver CPLEX v9.1, with the use of branch and bound method.

Details

Applications of Management Science
Type: Book
ISBN: 978-1-78441-211-1

Keywords

Abstract

Details

Handbook of Transport Modelling
Type: Book
ISBN: 978-0-08-045376-7

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