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This article presents an integrated methodology for the inclusion of a facility′s interactions with the outside environment, and the impact of those interactions on the location of entrances and exits within the facility. For example, the outside interactions generated by shipping and receiving activities will significantly influence the location of facility ingress/egress points. The “practical layout planning” (PLP) methodology integrates both layout construction and improvement techniques. The principal idea in this methodology is that departments within a facility be “condensed” into a number of “points”. In the layout construction phase, the relative location of these points is determined using multifacility location theory, where the facility′s interactions with the outside environment are represented by “contact points” and the departments in the layout are analogous to the new facilities to be located. Once these relative departmental positions are obtained, the “points” are then adjusted for areas to obtain a constructed layout. In the improvement technique, intra‐departmental flows are optimised by the optimal location of ingress/egress points which are determined by again using multifacility location theory. Interdepartmental flow is optimised by minimising the distance between departments as indicated by their closest ingress/egress points. The objective is to obtain a minimum total flow‐cost by interchanging departmental locations without violating physical constraints. The PLP methodology is demonstrated with a modest example.

Facility location decisions are critical and should be taken after strategic evaluations. Globalization and integration of economies make such decisions further complex and risk prone. The purpose of this paper is to identify and assess the risk factors to be considered while taking new facility location decision associated with global supply chain and device the methodology. A grey-based multi-criteria decision-making (MCDM) approach is used for this purpose, which also takes in to account the uncertainty in decision making. Such approach enables final decision to be more real and practical. The paper also highlighted and discussed the criteria on the basis of which the management can select the best suitable site.

The risk factors related to facility location for a global firm are identified. To select the location of a global facility with least risk, grey-based MCDM approach is formulated. This grey-based MCDM is demonstrated using the hypothetical case of an industrial valve manufacturing global firm. The grey approach is used to analyse location alternatives based on various decision criteria for extracting comparative ranking.

The paper presents a tool for strategic and planning level. It helps supply chain managers to identify the risks related to a candidate location. Then it guides the supply chain manager at strategic level to find the least risky location for a manufacturing facility.

This paper demonstrates the grey-based MCDM approach for determining less risky location to locate a new manufacturing unit so that practitioners can use this approach for taking other strategic decisions. The supply chain configuration can be decided subsequently which will yield more practical results and the decision taken will be more fruitful for firm.

The extensive literature review reveals that there are many models in the literature that addressed the issue of risk minimization in supply chain, but it was also noticed that there are limited number of models that minimize risk in locating a global facility considering the uncertainty of data in decision making. This is the first time that grey-based MCDM approach is formulated and used to find most suitable facility location under risk.

There have been numerous extensions of the maximum covering location problem that has been developed in the last decade to deal with facility location. Most of the research, however, addresses a single attribute or objective. In the case when a single criterion such as minimizing average response time to access a service facility is insufficient to address the interests of the decision maker, multiple objectives must be employed. Qualitative factors like customer service and market demand as well as quantitative factors like distribution and operating costs need to be appropriately weighted and used in a mathematical programming model. We develop a multi‐objective model for a service facility location problem that simultaneously sites facilities and allocates demand for products from different customer zones. We apply this model to “real‐world” data and show the practical advantages of using this model to solve capacitated service logistics problems.

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.

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.

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.

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

Locating disaster response centers is one of the key elements of efficient relief operations. The location and infrastructure of the candidate facilities usually conform to the required criteria at different levels. This study aims to identify the criteria for the main and local distribution center location problem separately and prioritize each candidate distribution center using a hybrid multiple criteria decision-making approach.

The proposed model incorporates analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) under interval type-2 fuzzy sets (IT2FSs) to overcome the uncertainty of experts` judgments and expressions in the evaluations of candidate distribution centers. In the proposed approach, weights of the criteria are determined using type-2 fuzzy AHP and the candidate distribution centers are prioritized using type-2 fuzzy TOPSIS.

Transportation, cost, infrastructure and security are determined as the main criteria for the main distribution center location criteria. Cost, warehouse facilities and security are the main criteria for local distribution center location selection. Prioritization enables decision-makers to assess each alternative accordingly to be able to select the best locations/facilities for efficient disaster response operations.

This study proposes new multi-criteria decision support models for prioritizing disaster response distribution centers. IT2FSs are used to be able to reflect both the complexity and vagueness of disaster environment and expert opinions. Different support models are suggested for main and local distribution centers considering their different missions. The proposed methodology is applied in Istanbul city, Turkey, where a high-magnitude earthquake is expected.

Presents an AHP (analytical hierarchy process) decision model for facility location selection from the view of organizations which contemplate locations of a new facility or a relocation of existing facilities. The AHP model provides a framework to assist managers in analysing various location factors, evaluating location site alternatives, and making final location selections. The primary principle of the AHP model is to match decision‐makers’ preferences with location site characteristics. The model requires that a number of potential sites have been proposed. Alternatives are then evaluated and compared under both quantitative and qualitative factors to allow managers to incorporate managerial experiences and judgement in the solution process. Uses an example problem to illustrate the solution process. Addresses managerial implications for future research.

Facility location and re-location decisions are critical managerial decisions in modern supply chains. Such decisions are difficult in this environment as managers encounter uncertainty and risks. The study investigates establishing or moving distribution facilities in the global supply chain by considering costs, fulfilment, trade uncertainties, risks under environmental trade-offs and disruptive technologies.

This paper combines the possibilities and probabilistic scenarios for a supply chain network by proposing the novel Robust Optimisation and Mixed Integer Linear Programming (ROMILP) method developed under the potential uncertainty of demand while considering the costs associated with a four-tier supply chain network. ROMILP has been solved in a real-time logistics environment by applying a case study approach.

The solution is obtained using an exact solution approach and provides optimality in all tested market scenarios along the proposed global logistics corridor. A sensitivity analysis examines potential facility location scenarios in a global supply chain context.

Logistics managers can apply the ROMILP model to test the cost-benefit trade-offs against their facility location and relocation decisions while operating under uncertainty. Future research is proposed to extend the literature by applying data from the OBOR logistics corridor.

This study is the first to examine sustainable dimensions along the global logistics corridor and investigate the global container traffic perspective. The study also adds value to the Middle East logistics corridor regarding facility location decisions.

The purpose of this paper is to present issues and challenges faced during a firm’s facility relocation decision aimed at improving both cost and service performance in an innovative service context.

The reader is given background of the decision-making process behind single service facility relocation decision using a detailed case study. Key financial, operational and business data of the firm are collected, compiled and analysed. The solution methodology uses a combination of qualitative and quantitative analyses to choose the best among the three possible discrete location choices. For propriety reasons, some information has been disguised, and some data have been sanitized.

The factors that significantly influence relocation decision are proximity to high transaction customers, infrastructure and other input costs, customer service level requirements and extant regulations. Transportation has a direct impact on cost as well as service level. Most of the findings are in line with literature, but some of them differ too.

The approach is focused on a single case study of a pooling container firm in the Indian context and thereby limits the ability to generalize the findings. Nevertheless, this study may serve as a significant starting point for future research.

Firms can create a rational, efficient and even-handed approach for relocation of facilities applying a mix of qualitative and quantitative models judiciously. It provides managers better understanding and insights and actions needed for single service facility relocation.

This work is perhaps the first on facility relocation in emerging economies covering actual interventions and experiences. It gives new insights to a limited literature of relocating single service facility reflecting both theoretical imperatives and practitioner requirements.

Rapid changes in today’s global markets are forcing businesses to re‐examine and improve the ways they compete. Integration of facility location decisions in global marketing and manufacturing strategies provides an important means for firms to compete in global markets. This paper proposes that manufacturing utility can be related to marketing utility through facility location decisions. Consequently, it presents a mathematical model for global facility location that integrates marketing and manufacturing decisions in a global context. It also presents a four‐stage evolutionary model that can guide managers in making global facility location decisions.

For many years, facilities location problems have attracted a great deal of attention in the literature. As a result, there is now a variety of methods for solving these problems. However, due to the recent interest, little research is found relating to the issues concerning international facilities location problems. Furthermore, in spite of the extensive modelling work done on facilities location, little modelling research exists on location problems. Provides a capacitated multi‐period, 0‐1 mixed integer programming formulation for the international facilities location problem and discusses its applications to an actual company case. This application is carried out to demonstrate not only how the model can be applied in practice but also to show its potential benefits when compared to other methods.