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Article
Publication date: 4 December 2017

Abdelrahman E.E. Eltoukhy, Felix T.S. Chan, S.H. Chung, Ben Niu and X.P. Wang

The purpose of this paper is twofold. First, to propose an operational model for aircraft maintenance routing problem (AMRP) rather than tactical models that are commonly used in…

Abstract

Purpose

The purpose of this paper is twofold. First, to propose an operational model for aircraft maintenance routing problem (AMRP) rather than tactical models that are commonly used in the literature. Second, to develop a fast and responsive solution method in order to cope with the frequent changes experienced in the airline industry.

Design/methodology/approach

Two important operational considerations were considered, simultaneously. First one is the maximum flying hours, and second one is the man-power availability. On the other hand, ant colony optimization (ACO), simulated annealing (SA), and genetic algorithm (GA) approaches were proposed to solve the model, and the upper bound was calculated to be the criteria to assess the performance of each meta-heuristic. After attempting to solve the model by these meta-heuristics, the authors noticed further improvement chances in terms of solution quality and computational time. Therefore, a new solution algorithm was proposed, and its performance was validated based on 12 real data from the EgyptAir carrier. Also, the model and experiments were extended to test the effect of the operational considerations on the profit.

Findings

The computational results showed that the proposed solution algorithm outperforms other meta-heuristics in finding a better solution in much less time, whereas the operational considerations improve the profitability of the existing model.

Research limitations/implications

The authors focused on some operational considerations rather than tactical considerations that are commonly used in the literature. One advantage of this is that it improves the profitability of the existing models. On the other hand, identifying future research opportunities should help academic researchers to develop new models and improve the performance of the existing models.

Practical implications

The experiment results showed that the proposed model and solution methods are scalable and can thus be adopted by the airline industry at large.

Originality/value

In the literature, AMRP models were cast with approximated assumption regarding the maintenance issue, while neglecting the man-power availability consideration. However, in this paper, the authors attempted to relax that maintenance assumption, and consider the man-power availability constraints. Since the result showed that these considerations improve the profitability by 5.63 percent in the largest case. The proposed operational considerations are hence significant. Also, the authors utilized ACO, SA, and GA to solve the model for the first time, and developed a new solution algorithm. The value and significance of the new algorithm appeared as follow. First, the solution quality was improved since the average improvement ratio over ACO, SA, and GA goes up to 8.30, 4.45, and 4.00 percent, respectively. Second, the computational time was significantly improved since it does not go beyond 3 seconds in all the 12 real cases, which is considered much lesser compared to ACO, SA, and GA.

Details

Industrial Management & Data Systems, vol. 117 no. 10
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 7 June 2019

Felix T.S. Chan, Zhengxu Wang, Yashveer Singh, X.P. Wang, J.H. Ruan and M.K. Tiwari

The purpose of this paper is to develop a model which schedules activities and allocates resources in a resource constrained project management problem. This paper also considers…

479

Abstract

Purpose

The purpose of this paper is to develop a model which schedules activities and allocates resources in a resource constrained project management problem. This paper also considers learning rate and uncertainties in the activity durations.

Design/methodology/approach

An activity schedule with requirements of different resource units is used to calculate the objectives: makespan and resource efficiency. A comparisons between non-dominated sorting genetic algorithm – II (NSGA-II) and non-dominated sorting genetic algorithm – III (NSGA-III) is done to calculate near optimal solutions. Buffers are introduced in the activity schedule to take uncertainty into account and learning rate is used to incorporate the learning effect.

Findings

The results show that NSGA-III gives better near optimal solutions than NSGA-II for multi-objective problem with different complexities of activity schedule.

Research limitations/implications

The paper does not considers activity sequencing with multiple activity relations (for instance partial overlapping among different activities) and dynamic events occurring in between or during activities.

Practical implications

The paper helps project managers in manufacturing industry to schedule the activities and allocate resources for a near-real world environment.

Originality/value

This paper takes into account both the learning rate and the uncertainties in the activity duration for a resource constrained project management problem. The uncertainty in both the individual durations of activities and the whole project duration time is taken into consideration. Genetic algorithms were used to solve the problem at hand.

Details

Industrial Management & Data Systems, vol. 119 no. 6
Type: Research Article
ISSN: 0263-5577

Keywords

Abstract

Details

Strategic Information System Agility: From Theory to Practices
Type: Book
ISBN: 978-1-80043-811-8

Article
Publication date: 9 February 2023

Xinsheng Xu, Ping Ji and Felix T.S. Chan

Optimal ordering decision for a retailer in a dual-sourcing procurement is an important research area. The main purpose of this paper is to explore a loss-averse retailer’s…

Abstract

Purpose

Optimal ordering decision for a retailer in a dual-sourcing procurement is an important research area. The main purpose of this paper is to explore a loss-averse retailer’s ordering decision in a dual-sourcing problem.

Design/methodology/approach

For a loss-averse retailer, the study obtains the optimal ordering decision to maximize expected utility. Based on sensitivity analysis, the properties of the optimal ordering decision are well discussed.

Findings

Under the optimal ordering quantity that maximizes expected loss aversion utility, the relevant expected profit of a retailer turns to be smaller under a bigger loss aversion coefficient. For this point, a retailer needs to balance between expected loss aversion utility maximization and expected profit maximization in deciding the optimal ordering policy in a dual-sourcing problem.

Originality/value

This paper reveals the influence of loss aversion on a retailer’s ordering decision in a dual-sourcing problem. Managerial insights are suggested to devise the optimal ordering policy for retailers in practice.

Details

Industrial Management & Data Systems, vol. 123 no. 3
Type: Research Article
ISSN: 0263-5577

Keywords

Content available
Book part
Publication date: 19 March 2019

Sadia Samar Ali, Rajbir Kaur and Jose Antonio Marmolejo Saucedo

Abstract

Details

Best Practices in Green Supply Chain Management
Type: Book
ISBN: 978-1-78756-216-5

Article
Publication date: 28 June 2022

Xinsheng Xu, Ping Ji and Felix T.S. Chan

With the rapid development of e-commerce, multi-sourcing with supply contracts and spot buying has become more and more popular in reality. The main purpose of the paper is to…

Abstract

Purpose

With the rapid development of e-commerce, multi-sourcing with supply contracts and spot buying has become more and more popular in reality. The main purpose of the paper is to explore a loss-averse buyer's optimal procurement policy in a multi-sourcing under e-commerce surroundings.

Design/methodology/approach

The study introduces the loss aversion utility function to characterize the loss aversion effect and derives a loss-averse buyer's optimal procurement policy in a multi-sourcing with a wholesale price contract and spot market.

Findings

A loss-averse buyer could order no items in a wholesale price contract and only needs to replenish commodities from spot market under certain conditions. In addition, the study shows that spot capacity has important influences on a loss-averse buyer's optimal ordering decision in the wholesale price contract.

Originality/value

This is the first paper to study the loss aversion effect on a buyer's procurement decision in a multi-sourcing. The results present important managerial insights for a loss-averse buyer to devise optimal ordering policies in a multi-sourcing under e-commerce surroundings.

Details

Industrial Management & Data Systems, vol. 122 no. 8
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 11 February 2019

Md. Tanweer Ahmad and Sandeep Mondal

This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining…

Abstract

Purpose

This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.

Design/methodology/approach

An integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.

Findings

The ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.

Practical implications

This paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.

Originality/value

It provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

Details

Journal of Modelling in Management, vol. 14 no. 1
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 3 August 2020

Yichen Qin, Hoi-Lam Ma, Felix T.S. Chan and Waqar Ahmed Khan

This paper aims to build a novel model and approach that assist an aircraft MRO procurement and overhaul management problems from the perspective of aircraft maintenance service…

Abstract

Purpose

This paper aims to build a novel model and approach that assist an aircraft MRO procurement and overhaul management problems from the perspective of aircraft maintenance service provider, in order to ensure its smoothness maintenance activities implementation. The mathematical model utilizes the data related to warehouse inventory management, incoming customer service planning as well as risk forecast and control management at the decision-making stage, which facilitates to alleviate the negative impact of the uncertain maintenance demands on the MRO spare parts inventory management operations.

Design/methodology/approach

A stochastic model is proposed to formulate the problem to minimize the impact of uncertain maintenance demands, which provides flexible procurement and overhaul strategies. A Benders decomposition algorithm is proposed to solve large-scale problem instances given the structure of the mathematical model.

Findings

Compared with the default branch-and-bound algorithm, the computational results suggest that the proposed Benders decomposition algorithm increases convergence speed.

Research limitations/implications

The results among the same group of problem instances suggest the robustness of Benders decomposition in tackling instances with different number of stochastic scenarios involved.

Practical implications

Extending the proposed model and algorithm to a decision support system is possible, which utilizes the databases from enterprise's service planning and management information systems.

Originality/value

A novel decision-making model for the integrated rotable and expendable MRO spare parts planning problem under uncertain environment is developed, which is formulated as a two-stage stochastic programming model.

Details

Industrial Management & Data Systems, vol. 120 no. 9
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 12 March 2024

Yanping Liu, Bo Yan and Xiaoxu Chen

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of…

Abstract

Purpose

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

Design/methodology/approach

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

Findings

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

Practical implications

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

Originality/value

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

Details

International Journal of Retail & Distribution Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-0552

Keywords

Article
Publication date: 1 January 2008

Adisak Theeranuphattana and John C.S. Tang

This paper revisits the recent work of Chan and Qi which proposed an innovative performance measurement method for supply chain management. While the measurement method has many…

5891

Abstract

Purpose

This paper revisits the recent work of Chan and Qi which proposed an innovative performance measurement method for supply chain management. While the measurement method has many advantages, it can be unwieldy in practice. This paper aims to address these limitations and to propose a more user‐friendly alternative performance measurement model.

Design/methodology/approach

The performance measurement model described in this paper is a combination of two existing methods: Chan and Qi's model and the supply chain operations reference (SCOR) model. To demonstrate the applicability of the combined approach, actual SCOR level 1 performance data and the measurement information from a case supply chain (SC) are collected and processed by Chan and Qi's measurement algorithm.

Findings

These two methods complement each other when measuring SC performance.

Originality/value

This paper develops a practical and efficient measurement model that can resolve SC performance problems by incorporating the strengths of two different measurement models to create a synergistic new model.

Details

Journal of Manufacturing Technology Management, vol. 19 no. 1
Type: Research Article
ISSN: 1741-038X

Keywords

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