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The multiple objective decision making problem arises when two or more non‐comparable objective functions are to be simultaneously optimised. There is a definite trend towards utilising interactive techniques for solving the multiple objective decision making problem. Interactive techniques allow the involvement of the DM throughout the decision process. In this paper we first provide a brief overview of multiple objective decision making, and then give a survey of literature dealing with interactive multiple objective decision making from 1965 to 1988.

Airspace sectorization is an important task, which has a significant impact in the everyday work of air control services. Especially in recent years, because of the constant increase in air traffic, existing airspace sectorization techniques have difficulties to tackle the large air traffic volumes, creating imbalanced sectors and uneven workload distribution among sectors. The purpose of this paper is to propose a new approach to find optimal airspace sectorization balancing the traffic controller workload between sectors, subject to airspace requirements.

A constraint programming (CP) model called equitable airspace sectorization problem (EQASP) relies on ordered weighted averaging (OWA) multiagent optimization and the parallel portfolio architecture has been developed, which integrates the equity into an existing CP approach (Trandac et al., 2005). The EQASP was evaluated and compared with the method of Trandac et al. (2005), according to the quality of workload balancing between sectors and the resolution performance. The comparison was achieved using real air traffic low-altitude network data sets of French airspace for five flight information regions for 24 h a day and the Algerian airspace for three various periods (off peak hours, peak hours and 24 h).

It has been demonstrated that the proposed EQASP model, which is based on OWA multicriteria optimization method, significantly improved both the solving performance and the workload equity between sectors, while offering strong theoretical properties of the balancing requirement. Interestingly, when solving hard instances, our parallel sectorization tool can provide, at any time, a workable solution, which satisfies all geometric constraints of sectorization.

This study can be used to design well-balanced air sectors in terms of workload between control units in the strategic phase. To fulfil the airspace users’ constraints, one can refer to this study to assess the capacity of each air sector (especially the overloaded sectors) and then adjust the sector’s shape to respond to the dynamic changes in traffic patterns.

This theoretical and practical approach enables the development and support of the definition of the “Air traffic management (ATM) Concept Target” through improvements in human factors specifically (balancing workload across sectors), which contributes to raising the level of capacity, safety and efficiency (SESAR Vision of ATM 2035).

In their approach, the authors proposed an OWA-based multiagent optimization model, ensuring the search for the best equitable solution, without requiring user-defined balancing constraints, which enforce each sector to have a workload between two user-defined bounds (W_min, W_max).

This paper aims to systematically understand the development of rapid setup, quantitatively analyze the landscape and reveal new trends and challenges.

Based on 192 literature studies (1987–2021) collected from Scopus and Google Scholar, the papers are classified by: publication time and source; research type and data analysis of papers; pattern of authorship and country; sector-wise focus of the paper; improvement method used in the setup. And CiteSpace is used to analyze the cooccurrence and timeline of keywords.

There has been substantial progress in the past 35 years, including the rapid growth in the number of papers, the expansion in different disciplines, the participation of developing countries, the application in the service industry and the significant impact of setup on cost. And there are still some deficiencies.

There is concern that Google Scholar lacks the quality control needed for its use as a bibliometric tool. Future work is encouraged to conduct an in-depth discussion on high-quality papers.

In small batch production, rapid setup is increasingly essential. Clarifying the research focus and main improvement methods is of great significance for enterprises to meet the changing market needs.

To the best of the authors’ knowledge, this study is the first literature review on rapid setup. It is decided to consider a detailed set of data for better introspection and trace the history reflections and the research future in setup time.

The purpose of this study is modelling of a problem of policing strategy order using a multicriteria method.

For the construction of the impact matrix strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria PROMETHEE II method was used, which with the help of the Visual PROMETHEE software, emulated the systematised data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision makers.

As a result, this research revealed that radio patrol, when used in a non-randomised manner, is the most effective policing strategy in reducing the 18 criminal demands studied in the perception of decision makers after data emulation with the PROMETHEE II method.

As research implications, it can be inferred that the use of multicriteria methods in the modelling of problems in public security area can contribute to the rationalisation of use of the available means in the fight against crime in large cities. This research showed that it is possible to use customised policing strategies to absolute reality.

The practical impact of this research lies in optimising the resources available to law enforcement agencies in the fight against crime in general.

It can be inferred that by choosing appropriate strategies to combat local crime, there is a direct implication in optimising the resources that the government makes available to police agencies. This optimisation allows pressure reduction under the public budget for more features. The model for choosing more effective strategies contributes to local crimes decrease, increasing the sense of the population security.

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices and in their associated use in ordering strategies through a multicriteria method. This study contributed to applied police intelligence.

This study aims to deal with a project portfolio selection problem aiming to maximize the net present value of the project portfolio and minimize the resource usage variation between successive time periods.

A bi-objective mixed integer programming model is presented under resource constraints. The parameters related to outlays and net cash flows of existing and new projects are considered to be uncertain. An augmented ε-constraint (AUGMECON) method is used to solve the proposed model, and a fuzzy approach is used to find the most preferred Pareto-optimal solutions among those generated by AUGMECON method. The effectiveness of the proposed solution method is compared with three other multi-objective optimization methods. Finally, some sensitivity analyses are performed to assess the effect of changing a number of parameters on the values of objective functions.

The proposed approach helps corporations make optimal decisions for rebalancing their project portfolio, through launching some new candidate projects and upgrading some of the existing projects.

A novel bi-objective optimization model is proposed for designing a project portfolio problem under budget constraints and profit risk controls. Two types of projects including existing and new projects are considered in the problem. Minimization of resource usage variation between successive periods is considered in the model as one objective function. An AUGMECON method is used to solve the proposed bi-objective mathematical model. A fuzzy approach is applied to find the best Pareto-optimal solutions of AUGMECON method. Results of the proposed solution approach are compared with three other multi-objective decision-making methods in different numerical examples.

This study aims to focus on the application of a multiple criteria decision analysis (MCDA) method to compare results presented by the Integrated Goals System based on the 12th edition of the Integrated Public Safety Areas (IPSAs) Award, which achieved goals established for Strategic Crime Indicators for the state of Rio de Janeiro, Brazil. The main objective of this research was to limit the compensatory effects of classification criteria on IPSAs that have achieved goals established for crime indicators by applying the MCDA method.

The methodology was based on the application of MCDA. The MCDA method selected and used was ELECTRE III, being implemented by J-Electre software.

Compared to results of the current method, the results of the ELECTRE III method showed a 94.87 per cent change in ranking positions revealed via the SIM method. This finding denotes the elimination of compensatory effects of the criteria. As a consequence, it can be affirmed that the application of resources by IPSA managers to reduce the prevalence of a single strategic crime indicator is no longer a success factor for awarding in the established goal system.

As limitations, it is possible to indicate the time cut used to carry out the research. The research may be extended to other issues of the productivity award.

The methodology applied with the use of ELECTRE III revealed that the government could reduce the cost with the incentive program to reduce criminal indices.

As the MCDA method is based on a binary pairwise comparison system, the methodology imposes a change of attitude on local managers fighting crime to reduce crime indicators and to consequently build a local sense of safety in IPSAs.

This research fills a gap in the literature because there are few studies using the MCDA method in the field of public security. The value of the work lies in the creation of a method that gives the decision-maker, of the law enforcement agency, an alternative to improve the process of rewarding by productividad of the integrated areas of public security.

The present study examines the concept of internal market orientation (IMO) and its effects on organisational performance comprising job satisfaction and employees' loyalty in the small and medium enterprises (SMEs) research context. Rooted in administrative theory, human relations theory, conventional theories of IMO and internal marketing, this study develops a novel iIMO theoretical framework that evinces the proliferation of ICTs in SMEs.

The proposed concept was empirically investigated by means of surveying 316 SME employees with the application of a multi-stage sampling procedure.

Research findings confirmed the viability of the ICT-supported iIMO framework, its positive effects on SMEs' organisational performance, and exhibited ample empirical evidence for the proficiency of the iIMO concept and its suitability for operationalisation by SMEs.

This study introduces ICTs as a novel IMO dimension which considers the undergoing holistic digitalisation of businesses. In addition, the present research posits the plausibility and confirms the benefits that arise following iIMO implementation in SMEs.

Following the study in Ref. 1 the optimization of a panweight network is further studied. A generalized fundamental equation is first defined. A sufficient condition and two necessary conditions are then supplied under which the policy obtained by the fundamental equation must be optimum. Finally, the relation between the fundamental equation and the optimum principle is discussed in detail.

As global markets become more customer oriented, rapid response rates are now often among the most important metrics in business. To achieve the required agility, many companies are forced to take decisions of whether to vertically integrate a value chain or to outsource some of its operations. The purpose of this paper is to develop a sequential decision modeling process to enable determination of optimal outsourcing policy decisions with respect to the variables such as warehouse inventory, in‐house manufacturing capacity and the ordering cost to the outsource supplier.

In this paper, a discrete dynamic programming‐based modeling framework is developed for analyzing outsourcing policies for supply chain management problems. Specifically, the assumed situation entails a dynamic decision between in‐house production vis‐à‐vis outsourcing, which is contingent upon several factors such as demand during the period under consideration, available inventory, available production capacity of the firm, ordering cost to the outsourced supplier and the fixed capital cost of machine capacity enhancement.

The framework enables the determination of a time‐based outsourcing policy, which is a prescription regarding: the optimum quantities to be produced in‐house vs those to be outsourced, and the level of capacity to be set in each period.

The problem investigates useful managerial decisions that are relevant to a real life dynamic situation within a manufacturing industry when effecting outsourcing decisions.

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.

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.

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.

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.

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.