Tactical Planning Research Articles

Simulation-aided machine learning: Applications in underwater acoustic perception and explainability

Underwater acoustic applications of machine learning are challenging due to sparsity, lack of diversity, and often uncertain labeling of training data. This is due to low levels of consumer relevance. One approach to the problem is to collect and label more data. However, this is expensive and unlikely to fully address the issue. A complementary approach is to use simulation for generating synthetic data and augmenting the machine learning pipeline. This also enables explainability by encoding human knowledge of the underlying physics. We present two case studies in simulation-aided machine learning. The first is an application to underwater munition dumpsite characterization using multi-view sonar surveys. Self-supervised learning has been used to pre-train a generative deep neural network to predict alternate views using unlabeled data. Subsequently, training is completed using a small volume of labelled data. Simulation was necessary for successful pre-training to continuously fill viewing angle gaps caused by limited and rigid survey directions. The second application is autonomous tactical planning for uncrewed underwater vehicles. Reinforcement learning policies have been trained to passively detect and localize underwater acoustic sources. These have been trained and evaluated in a fully synthetic environment, using a sophisticated propagation model together with empirical environmental parameters.

Prospects for improving the state regulation of foreign economic activities in Ukraine through the prism of ensuring the economic security of the state

The purpose of this article is to establish the directions of state regulation of foreign exchange, highlight the features of state regulation of foreign exchange, and determine the prospects for improving the mechanism of state regulation of foreign exchange in Ukraine. It has been determined that the ED is a complex complex type of activity that includes various objects and can be stratified into segments taking into account a number of criteria and features. At the same time, what is in demand is not the study of individual areas of regulation of foreign economic activity, but the analysis of their interaction. During the implementation of the FEZ, the achievement of the fundamental goal is significant - such activity should become a source of increasing national income and sustainable development of the economy. This has a perspective only in the course of solving tasks to achieve this goal, which is unattainable without a balanced and effective state administration. It has been proven that the State regulation of foreign trade includes a set of measures that have a legislative, executive and control nature, and are aimed at improving foreign trade in the interests of the country's economy. This system provides for the creation of the necessary conditions and mechanisms for the effective interaction of business entities within different states and at the international level. It has been established that the main directions of foreign economic activity are entrepreneurial activity, foreign trade, provision of various services, financial and credit operations, scientific and technical cooperation with foreign enterprises, etc. Regulation of these types of activities is carried out by the state through its bodies. Also, non-state subjects of economic management are involved in the regulation of foreign exchange, including: stock exchanges, chambers of commerce, associations, etc. The regulation of FEZ takes place together with FEZ subjects themselves on the basis of agreements concluded between them on the coordination of actions. It was emphasized that the essential components of the FED management mechanism are the systematic monitoring of the external and internal environment, the analysis and assessment of the state and development prospects of the FED, the development of tactical and strategic plans. It is legitimate to claim that the active digitization of the economy can provide advantages in the implementation of foreign trade in Ukraine.

A bi-objective robust model for minimization of costs and emissions of syngas supply chain

Producing syngas from forest-based biomass could facilitate the transitions in energy and forest sectors by replacing natural gas; reducing emissions and wastes; and generating revenues. Optimizing the economic and environmental impacts of the biomass supply chains can help realizing these benefits. In this study, a bi-objective robust optimization model is developed for tactical supply chain planning of forest biomass gasification at a pulp mill. It optimizes the monthly flow, inventory, and preprocessing of biomass while minimizing annual costs and emissions. Robust optimization with an adjustable risk of constraint violation is used to model the uncertainties in supply and cost of biomass. The average cost and emissions of the robust Pareto-optimal solutions are 68% and 41% higher than those in the deterministic solutions, respectively. Although, the cost and emissions and their trade-off in the deterministic case are more favorable, the robust solutions ensure no biomass shortage while avoiding over-conservatism.

Strategy Implementation Drivers and Performance of Kenya Airport Authority: A Case of Moi International Airport Mombasa County, Kenya

Amidst ever-emerging airports dynamics that make competition stiffer day-by-day, airports can use variety of strategy implementation drivers to maximize their performance. Kenya Airport Authority developed a five-year tactical plan to improve the overall performance for the company. However, the expected outcomes have not been obtained. Many researchers have pointed out on strategic management process but very few have attempted to prove that strategy implementation can yield better results owning to the fact that Kenya Airports Authority largely contribute to the country’s economy. This prompted this research on strategy implementation drivers on performance of Kenya Airports Authority: A case of Moi International Airport, in Kenya’s Mombasa County. The following specific goals steered the study; strategic communication, strategic structures, strategic leadership, and strategic resources on performance of Kenya Airports Authority: A case of Moi International Airport, Mombasa County in Kenya. The balance scorecard model, open system theory, transformational leadership theory, and resource-based philosophy served as the study's guiding theories. Descriptive research methodology was employed in the study. 66 respondents from Moi International Airport made up the sample population. Due of the limited population, the researcher utilized a census research design. The information was gathered via a semi-structured questionnaire. A pilot study was undertaken to test and assess the data collection tool's accuracy. Descriptive and inferential statistics were used to analyze the data. The research results were presented using pie charts, tables, and graphs. The majority of respondents agreed with numerous performance indicators, including those for strategic communication, strategic structure, strategic leadership, and strategic resources. Correlation analysis found a statistically significant association between performance and strategic communication, strategic structure, strategic leadership and strategic resources. Further, the model summary revealed that 83.1% of disparity in the performance was due to changes in strategic communication, strategic structure, strategic leadership and strategic resources. A conclusion was made that adopting an excellent implementation driver’s yield better organizational performance. The researcher recommended that engaging employees in communication, adoption of a collaborative structure, deployment of strategic leaders, mobilizing and building networks of resources, could do this. The study outcomes will help airports’ management in improving their performance and gaining an advantage over competitors. The study's findings will be used as guidance for those who make policies as they come up with rules and regulations governing airports.

Tactical Forwarder Planning: A Data-Driven Approach for Timber Forwarding

Tactical planning in timber harvesting involves aspects related to forest macro-planning and, particularly, the allocation of resources and sequencing of activities, all of which affect the allocation of timber in forest yards and roads and the productivity of forest machines. Data-driven approaches encourage the use of information obtained from data to enhance decision-making efficiency and support the development of short-term strategies. Therefore, our investigation was intended to determine whether a data-driven approach can generate sufficient input for modeling forwarder productivity in timber forwarding in Pinus and Eucalyptus planted forests, to support tactical planning. We utilized 3812 instances of raw data that were generated over a 36-month period. The data were collected from 23 loggers who operated in Pinus and Eucalyptus planted forests. We applied 22 regression algorithms that applied a supervised learning method from an experimental machine learning approach to the data instances. We evaluated the fitted models using three performance metrics. Out of the tested algorithms, the default mode of light gradient boosting produced a root mean squared error of 14.80 m3 h−1, a mean absolute error of 2.70, and a coefficient of determination of 0.77. Therefore, data-driven methods adequately support forwarder productivity modeling in timber forwarding in planted forests and help forest managers with tactical planning.

Optimizing the battery charging and swapping infrastructure for electric short-haul aircraft—The case of electric flight in Norway

Recent advances in battery technology have opened the possibility for short-haul electric flight. This is particularly attractive for commuter airlines that operate in remote regions such as archipelagos or Nordic fjords where the geography impedes other means of transportation. In this paper we address the question of how to optimize the charging infrastructure (charging power, spare batteries) for an airline when considering a battery swapping system. Our analysis considers the expenditures needed for (i) the significant charging power requirements, (ii) spare aircraft batteries, (iii) the used electricity, and (iv) delay costs, should the infrastructure not be sufficient to accommodate the flight schedule. The main result of this paper is the formulation of this problem as a two-phase recourse model. This is required to account for the variation of the flight schedule throughout a year of operations. With this, both the strategic (infrastructure sizing) and tactical (battery recharge scheduling) planning are addressed The model is applied for Widerøe Airlines, with a network of 7 hub airports and 36 regional airports in Norway. The results show that a total investment of 4412 kW in electricity power supply and 25 spare batteries is needed for the considered network, resulting in a daily investment of €11700. We also quantify the benefits of considering an entire year of operations for our analysis, instead of just one congested day (7% cost reduction) or one average day of operations (31% reduction) at the most congested airport.

Tactical and operational planning of express intra-city package services

In this paper, we focus on routing and load planning associated with the tactical and operational planning of an express intra-city courier service provider that receives a large number of shipments on a daily basis and is committed to delivering them to their destinations given a short service guarantee. Tactical planning relies on high-level aggregated demand rates over long time periods and takes the form of a multi-commodity service network design where the goal is to identify one path per commodity while maximizing consolidation opportunities in the network. Commodities are transported on their paths by means of a series of continuously operating vehicle cycles, where the structure and number of such cycles are determined concurrently with commodity path assignment decisions in a mixed integer programming. A second model is designed to refine the time allocation along different segments of a commodity path allowing a potential reduction in the number of vehicles required to meet the service guarantee. In operational planning, the focus is narrowed down to a shorter time period, and the baseline plan obtained from the tactical planning phase is adjusted to better fit potential deviations in observed demand patterns compared to the aggregate patterns. Through an extensive computational study designed on the topology of a major US city, we observe that the plans designed at the tactical level guarantee high service levels, which are improved at the operational level by customizing the plan to the special characteristic of a day of operation.

A quasi-dynamic air traffic assignment model for mitigating air traffic complexity and congestion for high-density UAM operations

In spite of the significant effects of COVID-19, UAM operations are still expected to grow smoothly and healthily in the near future. If such dense UAM traffic relies on tactical planning to resolve conflicts in a decentralized control scheme, urban airspace could soon be heavily congested and airspace complexity could be overwhelming. In this paper, we propose a Quasi-dynamic Air Traffic Assignment (QATA) model, which aims to allocate traffic flows among air routes in the planning horizon in order to organize UAM traffic flows and reduce air traffic congestion and complexity within a centralized strategic planning scheme while meeting the demand and respecting some criteria. Firstly, UAM traffics are modeled as flows that operate on a 3D two-way UAM route network. Next, the QATA problem is formulated as an optimization problem involving network dynamics to minimize the air traffic complexity evaluated by the linear dynamical system and congestion defined by traffic density and energy consumption. A simulation-based rolling horizon framework is introduced to decompose the QATA problem into several modified static air traffic assignment problems in each time interval. In order to overcome the limitations of conventional dynamic traffic assignment algorithms, a simulated annealing algorithm using parallel computing and a novel neighborhood generation strategy is proposed to efficiently optimize the problem. By applying the model to a pre-designed large-scale UAM route network in Singapore’s urban airspace, Experimental studies demonstrate the performance of the proposed framework and its applicability. Parallel computing can achieve up to three times faster than the original algorithm. The proposed algorithm significantly reduces the value of the objective function by (32.20±0.29)% in 143.47±3.74 seconds at the 95% confidence interval of 100 experiments, far better compared to the representative conventional dynamic traffic assignment algorithms. This study could be useful to assist air traffic control authorities and air navigation service providers in addressing various issues in unmanned traffic management.

A Two-Stage Stochastic Linear Programming Model for Tactical Planning in the Soybean Supply Chain

Background: The soybean market is representative of the world. Brazil is the largest producer and exporter of this crop and has low production costs but high logistical costs, which are influenced mainly by transport costs. Added to these characteristics, the disputed grain supply, the possibility of crop failure, and the randomness of some parameters that influence the soybean supply chain make decisions even more challenging. Methods: To mathematically model this problem, we carried out an analysis of the scientific production related to grain supply chain and the models used to address the problem, as well as a document analysis and a case study. Results: This paper proposes a new two-stage stochastic linear programming model with fixed recourse for tactical planning in the soybean supply chain from the perspective of the shipper under take or pay contracts over a one-year time horizon. The first-stage variables are the grain purchasing decisions and the volumes of rail and road transportation hired in advance. The model addresses 243 scenarios derived from four uncertainty sources: the purchase and sale prices of raw agricultural products on the spot market, the probability of crop failure, and the external demand. Conclusions: The model is successfully applied to a soybean trade firm in Brazil with expected gain of US$4,299,720 when using the stochastic model instead of the deterministic model. The stochastic model protected the firm from take or pay fines and crop failures, contracting a smaller volume of rail transport than what the company does.

Tactical planning for dynamic technician routing and scheduling problems

We consider the tactical planning aspect of a dynamic technician routing and scheduling problem with a time horizon of several days. In this problem study, some tasks are known beforehand, while others arrive dynamically. The tactical planning is to schedule the known tasks, such that we minimize the overall driving distance while ensuring short service times for the dynamic tasks. Without tactical planning, the known tasks would be spread throughout the whole area as they are scheduled based on a first-come-first-serve principle. In this study, we partition the area into disjoint slices covering the full plane and then assign the slices to individual work days. The partitioning of the area will be constructed with a balanced sweep algorithm using two approaches: The first is based on a parallel sweep-line following a given angle, while the second is based on a rotating sweep-line around a given origin. To guide the partitioning, we aim to minimize the degree of dynamism, which in our case is defined by the number of dynamic tasks, the distance from known tasks to dynamic tasks, and the tightness of the time windows. The tactical planning is evaluated using real-life and synthetic clustered data, where some of the tasks are known beforehand, and some are dynamic. We benchmark the various partitioning approaches against the default strategy of serving all known tasks on a first-come-first-serve basis. Computational results are reported showing around a 10% reduction in driving distance when using tactical planning. Furthermore, we show that up to 70% of the technicians can have a non-dynamic work day, without a significant increase in driving distance.

Planning a low-carbon, price-differentiated supply chain with scenario-based capacities and eco-friendly customers

This paper examines a comprehensive supply chain planning and differential pricing problem with carbon emissions considering (inbound and outbound) transportation policies. It also incorporates customers' preferences regarding prices and products’ environmental attributes in a market-segmented setting. Furthermore, supply uncertainties (induced by COVID-19 epidemic) are incorporated into the supply chain resource allocation problem. A novel scenario-based mixed-integer non-linear programming model is developed to deal with challenges. Subsequently, an optimal tactical plan is obtained by employing two-stage stochastic programming and convex analysis, which are enhanced by the interval Hessian matrix. Our findings suggest that failing to account for supply uncertainty could lead to intolerable losses and compromise the sustainability of the business.

Theoretical principles of budgeting as a method of economic management of enterprise’s activity

The paper is devoted to the study of the theoretical foundations of budgeting as a method of economic management of the enterprise. It has been proven that in modern conditions, budgeting is aimed at increasing the efficiency of its activities in the current period and in the future. There are considered modern approaches to the interpretation of the budget and the budgeting process at the enterprise. The analysis of various literary sources regarding the definition of the concept of "budgeting" was carried out. Various approaches to revealing the economic essence of the concept of budgeting have been identified. It was found that disagreements related to the interpretation of the term budgeting system by scientists lead to differences in the identification of its functions. The following approaches to the interpretation of the essence of the budgeting process are distinguished: budgeting as a tool for planning the enterprise's activities; budgeting as a tool for operational and tactical planning; budgeting as a management method; budgeting as a management technology. Also, there are considered the economic essence of budgeting as a method of economic management of the enterprise's activities, aimed at forming a system of budgets for all areas of its activity. The task of budgeting is systematized, the elements of the budget system infrastructure at the enterprise are presented. A sequence of stages in the formation of the budget system aimed at optimizing the economic management of the enterprise is proposed. A sequence of stages in the formation of the budget system aimed at optimizing the economic management of the enterprise is proposed. On the basis of the conducted research, a modern conceptual approach to the definition of the concept of "budgeting system" was formed.

Note: Demonstrating analytics in a low-tech context–truck-routing for solid-waste collection in an Indian metropolis

This paper describes an approach to introducing analytics through various algorithms and applications to users in a low-tech environment as a first step toward understanding such a context. The South Delhi Municipal Corporation (SDMC) of New Delhi, India, have partitioned their collection points into “wards” or clusters, each served by a dedicated truck depot and manually routing trucks for solid waste collection within each ward, with the waste from all wards going to a single landfill. To demonstrate analytics in tactical planning, we implemented the nearest neighbor algorithm mimicking the manual process to provide the baseline cost. Thus, we presented two very different vehicle routing algorithms: (1) a simple but fast revised nearest neighbor algorithm that decreased the baseline total routing cost by 1.57 % and (2) an optimal but time-intensive algorithm using a mixed-integer-linear programming model, which decreased the total cost by 4.05 %. To demonstrate strategic planning, we tested the efficacy of the cluster structure of collection points by comparing its total routing cost (using the revised nearest neighbor algorithm) to that of other partitions obtained with Minimum Spanning Tree (MST) and K-medoids clustering. The existing wards provided a lower waste pickup cost than the alternative clusters we created, showing SDMC that their existing ward structure was sound.

A collaborative approach based on Shapley value for carriers in the supply chain distribution

This paper addresses the problem of horizontal collaboration between carriers at the tactical planning level of the supply chain distribution. The study focuses on the relationship between a shipper and many carriers used to serve the transport requests of several geographically distributed customers. A profit sharing mechanism based on game theory is proposed in order to implement win-win collaboration between the carriers. The Shapley value is used to fairly share the profit of the grand coalition between the carriers. The collaboration is supported by mixed-integer linear programming model for the transport planning of all possible coalitions consisted by the carriers. The transport plans and the profit of each carrier can be generated by model simulation. The validity of the collaboration is checked by the super-additivity property of the game in each experiment. According to the subcontracting is allowed or not, the experimentations are carried out in two different contexts with realistic data sets. The experimental results show that each carrier's profit improvement is significant for all experiments, and that the collaboration also improves the customer service rate.

METHODOLOGICAL APPROACHES TO THE FORMATION OF ANALYTICAL SUPPORT FOR MONITORING THE ACTIVITIES OF AGRICULTURAL ENTERPRISES

Introduction. In connection with the instability of many social and economic indicators, the presence of numerous disparities in the economy and the need to assess the effectiveness of state policy in the field of agricultural development, it is necessary to ensure constant monitoring and analysis of the processes taking place. To solve the existing problems of information and analytical provision of effective management of agricultural development, it is necessary to develop a new direction in the system of agricultural statistics in the form of monitoring, which, on the one hand, will allow the most accurate and prompt monitoring of situational moments, and on the other hand, will become a basis for qualitative analysis, modelling and forecasting of agricultural development. Methods. The following methods were used in the research process: monographic (when studying the experience and features of the formation of monitoring and control systems), the method of analysis and synthesis (when substantiating the involvement of monitoring and control instruments in their management); abstract and logical (when defining the architecture and architectonics of mechanisms and systems for monitoring and controlling the economic results of agricultural enterprises); theoretical generalization and comparison (when performing theoretical generalizations and formulating conclusions, improving the conceptual and categorical research apparatus); structural and logical (when studying the process of integration of monitoring and control tools into the management of the main activity of agrarian enterprises). Results. The monitoring results are the information base for the implementation of the planning block, in which the strategic task of reproducing its components on the given planning time horizon is solved due to the dynamic interrelationship of operational and tactical planning tasks of the material and technical base. The practical application of the developed recommendations will provide a comprehensive systematic approach to the formation of information support for the substantiation of management decisions regarding the provision of reproduction processes in agricultural enterprises and it will contribute to the rational use of the formed material and technical base and the provision of rational rates of its reproduction. Discussion. The restoration of the material and technical base of agricultural enterprises in the post-war period will be carried out at the expense of investors, mainly foreign. In this connection, there is a need to develop an information support system for monitoring the activities of agricultural enterprises. Keywords: agricultural enterprise, monitoring, analytical support, management decision, management.

STRATEGY FOR MANAGING REGIONAL COMPETITIVENESS DEVELOPMENT

Abstract. The studies of economists are mostly devoted to the issues of ensuring the proper level of competitiveness of the country and finding ways to increase Ukraine's competitiveness rating in the world ranking. At the same time, there are many unsolved problems related to the competitiveness of the country's regions and the need to develop a strategy for managing regional competitiveness development, which indicates the relevance of the topic of research. The purpose of the article is theoretical substantiation of the essence of regional competitiveness and the development of a strategy of regional competitiveness development. The article examines the essence of the concept of "competitiveness" in relation to various objects: country, region, enterprise, products. The competitive advantages of the region have been studied and determined. The indicators used to assess the level of competitiveness of the region are grouped into blocks. An algorithm for increasing the competitiveness of the region, presented in the form of successivesteps: determination of strategic level of the competitiveness of the region; identification of main consumers and buyers of regional production; determination and increase of strategic factors of competitiveness of the region; formation of a strategy of regional competitiveness development; activation of the quality of regional business environment; formation of competitive regional market, has been developed. The necessity ofstrategic planning of regional competitiveness development is proved, the tasks and main characteristics of strategic planning are clarified. A mechanism of strategic management of regional competitiveness development, which involves the following stages: determination of target indicators of regionaldevelopment; strategic assessment of regional competitiveness; execution of necessary measurements in the region; implementation and adjustment of strategic plan is proposed. A mechanism of tactical planning of regional competitiveness development, which involves the creation of an information base about the region; performance of SWOT analysis of the region; positioning of the region; development of marketing and logistics strategy; implementation of the developed plan and monitoring and control over its implementation, is developed.

A tactical planning model for fresh produce production considering productive potential and changing weather patterns

A tactical planning model for fresh produce production considering productive potential and changing weather patterns

Diagnosis and treatment of the giant malignant peripheral nerve sheath tumor in the anterior mediastinum: A case report

INTRODUCTION: Malignant peripheral nerve sheath tumor (MPNST) occurs in young and middle-aged people, more frequently in those with the genetic disease known as neurofibromatosis type 1 (NF1). Approximately, 50% of people with MPNST have NF1 and 13% of people with NF1 will get MPNST during their lifetime.
 CASE REPORT: A 30-year-old patient after surgery for MPNST of the right hip in 2013 was observed. In 2017, a relapse was detected, and combined treatment was performed, including surgical excision of the relapse and postoperative distance radiotherapy with a total focal dose of 66 Gy. In 2018, MPNST of the left femoral nerve was diagnosed, and the tumor was excised. In 2020, a chest X-ray diagnosed a single focus of localized opacity in the anterior mediastinum, adjacent to the right lung. Computed tomography (CT) was performed to further verify the neoplasm, which revealed a single hypodense focus in the anterior mediastinum, adjacent to the right lung. According to histological examination of a tumor biopsy obtained by transthoracic ultrasound-guided biopsy, MPNST was verified. Magnetic resonance imaging (MRI) with intravenous contrast enhancement, including real-time MRI, was performed to assess the invasion of the mass into soft tissues and vessels and to plan surgical treatment. The following surgeries were done: right thoracotomy, removal of a neoplasm of the anterior mediastinum with resection of the upper lobe of the right lung, and marginal resections of the lower lobe of the right lung. This case demonstrates a rare localization and non-standard instrumental diagnosis of mediastinal MPNST. Apart from CT scanning, the patient underwent MRI of the thoracic organs. MRI allows assessing the invasion of the neoplasm into the surrounding tissues. This cannot always be achieved by CT scans, including those with contrast enhancement. Invasion is an important component in the planning of further surgical treatment tactics.
 CONCLUSIONS: MPNST is a tumor with an aggressive course and a poor prognosis due to resistance to therapy. This clinical case demonstrates a rare localized MPNST with a recurrent course and metastases to the lungs. The current radiological methods, such as CT and MRI, may be used effectively both for diagnosing MPNST and determining the appropriate surgical access to the lesion and the extent of surgery.

Multi-period location routing: An application to the planning of mobile clinic operations in Iraq

Health service access and delivery are hampered during humanitarian crises due to disrupted health systems, damaged infrastructure, and healthcare worker shortages, this particularly in conflict zones. Mobile clinics are a strategy used to reach populations cut off from local health services, and organizations commonly rely on them during relief and recovery humanitarian efforts to deliver primary healthcare. In this study, we present a multiperiod location-routing problem (MLRP) with benefits for the tactical planning of mobile clinic deployment. Our set-packing formulation was developed and solved as part of a collaboration with Première Urgence Internationale (PUI). The proposed model aims to select communities to be served and design routes to be performed such that health benefits, measured by means of coverage and continuity of care functions, are maximized throughout the planning horizon. Results are presented for an application based on PUI’s operations in Iraq, including sensitivity analyses on the parameters used to model the healthcare benefits. Managerial insights on the impacts of organizational strategic and tactical decisions, such as the number of mobile clinics and the relative importance given to coverage and continuity of care, are presented.

Modelling and solving approaches for scheduling problems in reconfigurable manufacturing systems

Reconfigurable manufacturing systems (RMS) intend to bridge the gap between dedicated and flexible manufacturing systems. If the literature is mainly focused on the design step and tactical planning of such systems, few research projects have addressed scheduling at the operational level. While setup times may occur in flexible manufacturing systems, reconfiguration times considered in RMS may affect several resources at once, and hence require specific modelling and solving approaches to be considered. This paper first formalises the problem at hand through integer linear programming. An iterative search method is then provided to obtain solutions to larger-scale instances. Results obtained on generated instances show that managing even few possible configurations can yield significant improvements in solutions’ quality. Meanwhile, the extended search space implied by the increase in available configurations hinders the convergence to a good solution in a reasonable computation time, which suggests further investigations.