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Article
Publication date: 30 November 2018

Fang Yan, Yanfang Ma and Cuiying Feng

The purpose of this paper is to study a transportation service procurement bid construction problem from a less than a full truckload perspective. It seeks to establish stochastic…

Abstract

Purpose

The purpose of this paper is to study a transportation service procurement bid construction problem from a less than a full truckload perspective. It seeks to establish stochastic mixed integer programming to allow for the proper bundle of loads to be chosen based on price, which could improve the likelihood that carrier can earn its maximum utility.

Design/methodology/approach

The authors proposes a bi-level programming that integrates the bid selection and winner determination and a discrete particle swarm optimization (PSO) solution algorithm is then developed, and a numerical simulation is used to make model and algorithm analysis.

Findings

The algorithm comparison shows that although GA could find a little more Pareto solutions than PSO, it takes a longer time and the quality of these solutions is not dominant. The model analysis shows that compared with traditional approach, our model could promote the likelihood of winning bids and the decision effectiveness of the whole system because it considers the reaction of the shipper.

Originality/value

The highlights of this paper are considering the likelihood of winning the business and describing the conflicting and cooperative relationship between the carrier and the shipper by using a stochastic mixed integer programming, which has been rarely examined in previous research.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 30 no. 5
Type: Research Article
ISSN: 1355-5855

Keywords

Article
Publication date: 8 May 2019

Syed Mohd Muneeb, Mohammad Asim Nomani, Malek Masmoudi and Ahmad Yusuf Adhami

Supplier selection problem is the key process in decision making of supply chain management. An effective selection of vendors is heavily responsible for the success of any…

Abstract

Purpose

Supplier selection problem is the key process in decision making of supply chain management. An effective selection of vendors is heavily responsible for the success of any organization. Vendor selection problem (VSP) reflects a more practical view when the decision makers involved in the problem are present on different levels. Moreover, vendor selection consists of various random parameters to be dealt with in real life. The purpose of this paper is to present a decentralized bi-level VSP where demand and supply are normal random variables and objectives are fuzzy in nature. Decision makers are present at two levels and are called as leader and follower. As the next purpose, this paper extends and presents a solution approach for fuzzy bi-level multi-objective decision-making model with stochastic constraints. Different scenarios have been developed within a real-life case study based on different sets of controlling factors under the control of leader.

Design/methodology/approach

This study uses chance-constrained programming and fuzzy set theory to generate the results. Stochastic constraints are converted into deterministic constraints using chance-constrained programming. Decision variables in the bi-level VSP are partitioned between the two levels and considered as controlling factors. Membership functions based on fuzzy set theory are created for the goals and controlling factors and are used to obtain the overall satisfactory solutions. The model is tested on a real-life case study of a textile industry and different scenarios are constructed based on the choice of leader’s controlling factors.

Findings

Results showed that the approach is quite helpful as it generates efficient results producing a good level of satisfaction for the decision makers of both the levels. Results showed that on choosing the vendors that are associated with worst values in terms of associated costs, vendor ratings and quota flexibilities as controlling factors by the leaders, the level of satisfaction achieved is highest. The level of satisfaction of solution is lowest for the scenario when the leader chooses to control the decision variables associated with vendors that are profiled with minimum vendor ratings. Results also showed that higher availability of materials and budget with vendors proved helpful in obtaining quota allocations. Different scenarios generate different results along with different values of satisfaction degrees and objective values which shows the flexible feature of the approach based on leader’s choice of controlling factors. Numerical results showed that the leader’s control can be effectively incorporated maintaining satisfaction levels of the followers under various scenarios or conditions.

Research limitations/implications

The paper makes a certain contribution toward the study of vendor selection existing in a hierarchical manner under uncertain environment. A wide set of data of different factors is needed which can be seen as a limitation when the available time is short for the supplier selection process.

Practical implications

VSP which is generally adopted by most of the large organizations is characterized with hierarchical decision making. Moreover, dealing with the real-life concern, the data available for some of the parameters are not complete, representing an uncertainty of parameters. This study is quite helpful for decentralized VSP under uncertain environment to reduce the costs, improve profit margins and to create long-term relationships with selected vendors. The proposed model also provides an avenue to explore the decision making when the leader has control over some of the decision variables.

Originality/value

Reviewing the literature available, this is the first attempt to present a multi-objective VSP where the decision makers are at hierarchical levels considering uncertain parameters such as demand and supply as per the best knowledge of authors. This research further provides an approach to construct scenarios or different cases based on the choice of leader’s choice of controlling factors.

Article
Publication date: 11 April 2022

Amin Ahwazian, Atefeh Amindoust, Reza Tavakkoli-Moghaddam and Mehrdad Nikbakht

The purpose of this paper is to design petroleum products’ supply chain management, which includes efficient integration of suppliers, manufacturers, storehouses and retailers.

Abstract

Purpose

The purpose of this paper is to design petroleum products’ supply chain management, which includes efficient integration of suppliers, manufacturers, storehouses and retailers.

Design/methodology/approach

This paper proposes that a three-level supply chain will be turned into a bi-level supply chain of petroleum products by simultaneous integration of the middle level with the upstream and downstream levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels.

Findings

The concepts of the design, structure and outputs are led by the model's solution. The model also responds to the variations in the market via coordination in the related decisions to the distribution, production and inventory issues, and also coordinating between the demands and production.

Research limitations/implications

This paper has limited its analysis to definite values due to the over-expansion of calculations and analysis. Future works can study other aspects of the proposed model for a multi-level petroleum product supply chain in different states of certain parameters and time zones.

Practical implications

The designed model can directly and transparently help the oil managers and decision-makers lower the costs of manufacturing, distribution and sales with respect to the determined criteria.

Originality/value

This paper establishes that effectiveness of the dynamic petroleum materials supply chain design will increase by considering maintained and increased production costs and coordinate management flows at all levels by supply chain creation’s integration.

Details

Journal of Advances in Management Research, vol. 19 no. 4
Type: Research Article
ISSN: 0972-7981

Keywords

Article
Publication date: 31 May 2022

Harish Garg, Dang Ngoc Hoang Thanh and Rizk M. Rizk-Allah

The paper aims to introduce a novel concept to solve the bi-level multi-criteria nonlinear fractional programming (BL-MCNFP) problems. Bi-level programming problem (BLPP) is…

Abstract

Purpose

The paper aims to introduce a novel concept to solve the bi-level multi-criteria nonlinear fractional programming (BL-MCNFP) problems. Bi-level programming problem (BLPP) is rigorously flourished and studied by several researchers, which deals with decentralized decisions by comprising a sequence of two optimization problems, namely upper and lower-level problems. However, on the other hand, many real-world decision-making problems involve multiple objectives with fraction aspects, called fractional programming problems that reflect technical and economic performance.

Design/methodology/approach

This paper introduces a VIKOR (“VlseKriterijumska Optimizacija I Kompromisno Resenje”) approach to solve the BL-MCNFP problem. In this approach, an aggregating function based on LP metrics is formulated on the basis of the “closeness” scheme from the “ideal” solution. The three steps perform the solution process: First, a new concept is attempted to minimize and maximize of the numerators and denominators from their respective ideal solutions and anti-ideal values simultaneously. Second, for each level, the K-dimensional objective space of each level is converted to a one-dimensional space by an aggregating function. Third, to obtain the final solution, all levels are combined into single-level model where the decision variables of upper levels are interrelated with other levels through fuzzy strategy-based linear and nonlinear membership functions.

Findings

The effectiveness of the proposed VIKOR is demonstrated by numerical examples, where the reported results affirm that the extended VIKOR method provides superior results in comparison with the same methods in the literature, and it is a good alternative to BL-MCNFP problems.

Originality/value

In terms of the assistance-based right decision, a parametric analysis for the weight of the majority is provided to exhibit a wide range of compromise solutions for the decision-maker.

Details

Kybernetes, vol. 52 no. 10
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 12 June 2023

Sarasadat Alavi, Ali Bozorgi-Amiri and Seyed Mohammad Seyedhosseini

Fortification-interdiction models provide system designers with a broader perspective to identify and protect vital components. Based on this concept, the authors examine how…

Abstract

Purpose

Fortification-interdiction models provide system designers with a broader perspective to identify and protect vital components. Based on this concept, the authors examine how disruptions impact critical supply systems and propose the most effective protection strategies based on three levels of decision-makers. This paper aims to investigate location and fortification decisions at the first level. Moreover, a redesign problem is presented in the third level to locate backup facilities and reallocate undisrupted facilities following the realization of the disruptive agent decisions at the second level.

Design/methodology/approach

To address this problem, the authors develop a tri-level planner-attacker-defender optimization model. The model minimizes investment and demand satisfaction costs and alleviates maximal post-disruption costs. While decisions are decentralized at different levels, the authors develop an integrated solution algorithm to solve the model using the column-and-constraint generation (CCG) method.

Findings

The model and the solution approach are tested on a real supply system consisting of several hospitals and demand areas in a region in Iran. Results indicate that incorporating redesign decisions at the third level reduces maximum disruption costs.

Originality/value

The paper makes the following contributions: presenting a novel tri-level optimization model to formulate facility location and interdiction problems simultaneously, considering corrective measures at the third level to reconfigure the system after interdiction, creating a resilient supply system that can fulfill all demands after disruptions, employing a nested CCG method to solve the model.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 11 June 2018

Sujit Kumar De and Shib Sankar Sana

The purpose of this paper is to deal with profit maximization problem of two-layer supply chain (SC) under fuzzy stochastic demand having finite mean and unknown variance. Buyback…

Abstract

Purpose

The purpose of this paper is to deal with profit maximization problem of two-layer supply chain (SC) under fuzzy stochastic demand having finite mean and unknown variance. Buyback policy is employed from the retailer to supplier. The profit of the supplier solely depends on the order size of the retailers. However, the loss of shortage items is related to loss of profit and goodwill dependent. The authors develop the profit function separately for both the retailer and supplier, first, for a decentralized system and, second, joining them, the authors get a centralized system (CS) of decision making, in which one is giving more profit to both of them. The problem is solved analytically first, then the authors fuzzify the model and solve by fuzzy Hausdorff distance method.

Design/methodology/approach

The analytical models are formed for both centralized and decentralized systems under non-cooperative and cooperative environment with suitable constraints. A significant assumption on density function, namely Cauchy-type density function, is introduced for demand rate because of its wider range of the retailers’ satisfactions. Fuzzy Hausdorff metric is incorporated within the fuzzy components of the fuzzy sets itself. Using this method, the authors find out closure values of both centralized and decentralized policies, which is an essential part of any cooperative and non-cooperative two-layer SC models. Moreover, the authors take care of the profit values with corresponding ambiguities for both the systems explicitly.

Findings

It is found that the centralize policy of SC could only be able to maximize the profit of both the retailers and suppliers. All analytical results are illustrated numerically along with sensitivity analysis and side by side comparative studies between Hausdorff and Euclidean distance measure are done exclusively.

Research limitations/implications

The main focus of attention of the proposed model is given to usefulness of Hausdorff distance. Unlike other distances, Hausdorff distance can take special care on the similarity measures of different fuzzy sets. Researchers have been engaged to use Hausdorff distance on the different fuzzy sets but, in this study, the authors have used it within the components of a same fuzzy set to gain more closure values than other methods.

Originality/value

The use of this Hausdorff distance approach is totally new as per literature survey suggested yet. However, the Cauchy-type density function has not been introduced anywhere in SC management problems by modern researchers still now. In crisp model, the sensitivity on goodwill measures really provides a special attention also.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 11 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 10 August 2010

Nengchao Lv, Xinping Yan, Kun Xu and Chaozhong Wu

The purpose of this paper is to propose a bi‐level programming optimization model to reduce traffic congestion of transportation network while evacuating people to safe shelters…

1410

Abstract

Purpose

The purpose of this paper is to propose a bi‐level programming optimization model to reduce traffic congestion of transportation network while evacuating people to safe shelters during disasters or special events.

Design/methodology/approach

The previous optimization model for contra flow configuration only considered the character of the manager. However, the traffic condition is not only controlled by managers, but also depended on the root choice of travelers. A bi‐level programming optimization model, which considered managers and evacuees' character, is proposed to optimize the contra flow of transportation network in evacuation during special events. The upper level model aims to minimize the total evacuation time, while the lower level based on user equilibrium assignment. A solution method based on discrete particle swarm optimization and Frank‐Wolfe algorithm is employed to solve the bi‐level programming problem.

Findings

It is found that the bi‐level programming based contra flow optimization model can improve evacuation efficiency and decrease evacuation time 30 per cent or more. With the increase of traffic demand, the evacuation time will decrease significantly by contra flow configuration.

Research limitations/implications

In the optimization model, the background traffic is ignored for simplification and the contra flow is configured absolutely as 0 or 1, which ensures vehicles do not go back into the evacuation area.

Practical implications

An efficient optimization model for traffic managers to reduce congestion and evacuation time of evacuation network.

Originality/value

The new bi‐level programming model not only considers managers' character, but also considers evacuees' reaction. The paper is aimed to optimize contra flow for transportation network.

Details

Kybernetes, vol. 39 no. 8
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 28 May 2021

Zainab Asim, Syed Aqib Aqib Jalil, Shakeel Javaid and Syed Mohd Muneeb

This paper aims to develop a grey decentralized bi-level multi-objective programming (MOP) model. A solution approach is also proposed for the given model. A production and…

Abstract

Purpose

This paper aims to develop a grey decentralized bi-level multi-objective programming (MOP) model. A solution approach is also proposed for the given model. A production and transportation plan for a closed loop supply chain network under an uncertain environment and different scenarios is also developed.

Design/methodology/approach

In this paper, we combined grey linear programming (GLP) and fuzzy set theory to present a solution approach for the problem. The proposed model first solves the given problem using GLP. Membership functions for the decision variables under the control of the leader and for the goals are created. These membership functions are then used to generate the final solutions.

Findings

This paper provides insight for fomenting the decision-making process while providing a more flexible approach in uncertain logistics problems. The deviations of the final solution from the individual best solutions of the two levels are very little. These deviations can further be reduced by adjusting the tolerances associated with the decision variables under the control of the leader.

Practical implications

The proposed approach uses the concept of membership functions of linear form, and thus, requires less computational efforts while providing effective results. Most of the organizations exhibit decentralized decision-making under the presence of uncertainties. Therefore, the present study is helpful in dealing with such scenarios.

Originality/value

This is the first time, formulation of a decentralized bi-level multi-objective model under a grey environment is carried out as per the best knowledge of the authors. A solution approach is developed for bi-level MOP under grey uncertainty.

Details

Journal of Modelling in Management, vol. 16 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

Book part
Publication date: 15 December 1998

Xiaoyan Zhang and Mike Maher

This paper deals with two problems in transport network planning and control: trip matrix estimation and traffic signal optimisation. These two problems have both been formulated…

Abstract

This paper deals with two problems in transport network planning and control: trip matrix estimation and traffic signal optimisation. These two problems have both been formulated as bi-level programming problems with the User Equilibrium assignment as the second-level programming problem. One currently used method for solving the two problems consists of alternate optimisation of the two sub-problems until mutually consistent solutions are found. However, this alternate procedure does not converge to the solution of the bi-level programming problem. In this paper, a new algorithm will be developed and will be applied to two road networks.

Details

Mathematics in Transport Planning and Control
Type: Book
ISBN: 978-0-08-043430-8

Article
Publication date: 12 October 2012

Min Zhang, Jun Huang and Jian‐ming Zhu

The facility in an emergency system could be immobilized because of the huge destructive power of an irregular emergency and the uncertainty of the time, place and scale of…

Abstract

Purpose

The facility in an emergency system could be immobilized because of the huge destructive power of an irregular emergency and the uncertainty of the time, place and scale of occurrence. So facility failure scenarios must be considered at the time of location. The purpose of this paper is to establish a location model based on the worst facility failure, the objective of which is to minimize the cost and cover the demand maximally. It is demonstrated that location choice, considering facility failure, has significant meaning when considering economic benefit and covering the demand.

Design/methodology/approach

A bi‐level programming model which studies the facility location is established by using the methods of scenario analysis and robust optimization. It is compared with a classic location model, without considering facility failure, from the points of view of economic benefit and maximal covering demand.

Findings

Compared to the classic location model, without considering facility failure, it is demonstrated that the location model which considers facility failure can save more costs from the economic benefit point of view and, from the maximal covering of the demand point of view, has a higher covering ratio. So facility failure scenario should be considered in the location of an emergency facility.

Originality/value

The paper studies facility location based on the worst scenario, from the two aspects of economic benefits and maximal covering demand.

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