scholarly journals Multi-Objective Pharmaceutical Portfolio Optimization under Uncertainty of Cost and Return

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2339
Author(s):  
Mahboubeh Farid ◽  
Hampus Hallman ◽  
Mikael Palmblad ◽  
Johannes Vänngård
Keyword(s):  
Portfolio Optimization ◽  
Decision Makers ◽  
Optimization Under Uncertainty ◽  
Product Development Process ◽  
Multi Objective ◽  
Probability Of Success ◽  
Low Probability ◽  
Key Aspects ◽  
The Cost ◽  
Selection Of

This paper presents the study of multi-objective optimization of a pharmaceutical portfolio when both cost and return values are uncertain. Decision makers in the pharmaceutical industry encounter several challenges in deciding the optimal selection of drug projects for their portfolio since they have to consider several key aspects such as a long product-development process split into multiple phases, high cost and low probability of success. Additionally, the optimization often involves more than a single objective (goal) with a non-deterministic nature. The aim of the study is to develop a stochastic multi-objective approach in the frame of chance-constrained goal programming. The application of the results of this study allows pharmaceutical decision makers to handle two goals simultaneously, where one objective is to achieve a target return and another is to keep the cost within a finite annual budget. Finally, the numerical results for portfolio optimization are presented and discussed.

scholarly journals Pre-Selection of the Optimal Sitting of Phase-Shifting Transformers Based on an Optimization Problem Solved within a Coordinated Cross-Border Congestion Management Process

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3748 ◽  
Author(s):  
Endika Urresti-Padrón ◽  
Marcin Jakubek ◽  
Wojciech Jaworski ◽  
Michał Kłos
Keyword(s):  
Optimization Problem ◽  
Congestion Management ◽  
Decision Makers ◽  
Phase Shifting ◽  
Management Process ◽  
European Policy ◽  
Cross Border ◽  
Remedial Actions ◽  
The Cost ◽  
Selection Of

The current European policy roadmap aims at forcing the TSOs to coordinate remedial actions used for relieving the congestions in the synchronous power system. In this paper, an optimization problem for coordinated congestion management is described and its results obtained for a real European use cases created in the H2020 EU-SysFlex project are presented. First of all, these results prove the feasibility of a central optimization problem for the coordination of the cross-border congestion management process. Next, the formulated optimization problem is used to tackle the issue of planning the investments in phase-shifting transformers (PSTs), for the purpose of increasing the efficiency/decreasing the cost of congestion management. Finally, this paper introduces two optimization-based indicators for pre-selecting the investment sites, which may be used to support the decision makers aiming at decreasing the costs of coordinated congestion management.

scholarly journals Solving the Asymmetry Multi-Objective Optimization Problem in PPPs under LPVR Mechanism by Bi-Level Programing

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1667
Author(s):  
Feiran Liu ◽  
Jun Liu ◽  
Xuedong Yan
Keyword(s):  
Optimization Problem ◽  
Optimal Strategies ◽  
Decision Makers ◽  
Multi Objective Optimization ◽  
Pareto Solutions ◽  
Present Value ◽  
Public And Private ◽  
The Public ◽  
Multi Objective ◽  
The Cost

Optimizing the cost and benefit allocation among multiple players in a public-private partnership (PPP) project is recognized to be a multi-objective optimization problem (MOP). When the least present value of revenue (LPVR) mechanism is adopted in the competitive procurement of PPPs, the MOP presents asymmetry in objective levels, control variables and action orders. This paper characterizes this asymmetrical MOP in Stackelberg theory and builds a bi-level programing model to solve it in order to support the decision-making activities of both the public and private sectors in negotiation. An intuitive algorithm based on the non-dominated sorting genetic algorithm III (NSGA III) framework is designed to generate Pareto solutions that allow decision-makers to choose optimal strategies from their own criteria. The effectiveness of the model and algorithm is validated via a real case of a highway PPP project. The results reveal that the PPP project will be financially infeasible without the transfer of certain amounts of exterior benefits into supplementary income for the private sector. Besides, the strategy of transferring minimum exterior benefits is more beneficial to the public sector than to users.

Including decision-makers preferences in the cost-deprivation trade-off during disaster interventions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Florian Diehlmann ◽  
Patrick Siegfried Hiemsch ◽  
Marcus Wiens ◽  
Markus Lüttenberg ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Humanitarian Logistics ◽  
Decision Makers ◽  
Weighted Sum ◽  
Trade Off ◽  
Content Type ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
The Cost

Purpose In this contribution, the purpose of this study is to extend the established social cost concept of humanitarian logistics into a preference-based bi-objective approach. The novel concept offers an efficient, robust and transparent way to consider the decision-maker’s preference. In principle, the proposed method applies to any multi-objective decision and is especially suitable for decisions with conflicting objectives and asymmetric impact. Design/methodology/approach The authors bypass the shortcomings of the traditional approach by introducing a normalized weighted sum approach. Within this approach, logistics and deprivation costs are normalized with the help of Nadir and Utopia points. The weighting factor represents the preference of a decision-maker toward emphasizing the reduction of one cost component. The authors apply the approach to a case study for hypothetical water contamination in the city of Berlin, in which authorities select distribution center (DiC) locations to supply water to beneficiaries. Findings The results of the case study highlight that the decisions generated by the approach are more consistent with the decision-makers preferences while enabling higher efficiency gains. Furthermore, it is possible to identify robust solutions, i.e. DiCs opened in each scenario. These locations can be the focal point of interest during disaster preparedness. Moreover, the introduced approach increases the transparency of the decision by highlighting the cost-deprivation trade-off, together with the Pareto-front. Practical implications For practical users, such as disaster control and civil protection authorities, this approach provides a transparent focus on the trade-off of their decision objectives. The case study highlights that it proves to be a powerful concept for multi-objective decisions in the domain of humanitarian logistics and for collaborative decision-making. Originality/value To the best of the knowledge, the present study is the first to include preferences in the cost-deprivation trade-off. Moreover, it highlights the promising option to use a weighted-sum approach to understand the decisions affected by this trade-off better and thereby, increase the transparency and quality of decision-making in disasters.

scholarly journals Optimization of hydrometric monitoring network in urban drainage systems using information theory

2017 ◽  
Vol 76 (7) ◽  
pp. 1603-1613 ◽  
Author(s):  
J. Yazdi
Keyword(s):  
Urban Areas ◽  
Numerical Models ◽  
Monitoring Network ◽  
Cost Effective ◽  
Decision Makers ◽  
Modeling Framework ◽  
Optimal Monitoring ◽  
Shared Information ◽  
The Cost ◽  
Selection Of

Regular and continuous monitoring of urban runoff in both quality and quantity aspects is of great importance for controlling and managing surface runoff. Due to the considerable costs of establishing new gauges, optimization of the monitoring network is essential. This research proposes an approach for site selection of new discharge stations in urban areas, based on entropy theory in conjunction with multi-objective optimization tools and numerical models. The modeling framework provides an optimal trade-off between the maximum possible information content and the minimum shared information among stations. This approach was applied to the main surface-water collection system in Tehran to determine new optimal monitoring points under the cost considerations. Experimental results on this drainage network show that the obtained cost-effective designs noticeably outperform the consulting engineers’ proposal in terms of both information contents and shared information. The research also determined the highly frequent sites at the Pareto front which might be important for decision makers to give a priority for gauge installation on those locations of the network.

An effective multi-objective approach to prioritisation of sewer pipe inspection

2009 ◽  
Vol 60 (4) ◽  
pp. 841-850 ◽  
Author(s):  
L. Berardi ◽  
O. Giustolisi ◽  
D. A. Savic ◽  
Z. Kapelan
Keyword(s):  
Genetic Algorithm ◽  
Decision Makers ◽  
Sewer System ◽  
Multi Objective ◽  
Decision Context ◽  
Multi Objective Genetic Algorithm ◽  
Sewer Rehabilitation ◽  
Genetic Algorithm Approach ◽  
The Uk ◽  
The Cost

The first step in the decision making process for proactive sewer rehabilitation is to assess the condition of conduits. In a risk-based decision context the set of sewers to be inspected first should be identified based on the trade-off between the risk of failures and the cost of inspections. In this paper the most effective inspection works are obtained by solving a multi-objective optimization problem where the total cost of the survey programme and the expected cost of emergency repairs subsequent to blockages and collapses are considered simultaneously. A multi-objective genetic algorithm (MOGA) is used to identify a set of Pareto-optimal inspection programmes. Regardless of the proven effectiveness of the genetic-algorithm approach, the scrutiny of MOGA-based inspection strategies shows that they can differ significantly from each other, even when having comparable costs. A post-processing of MOGA solutions is proposed herein, which allows priority to be assigned to each survey intervention. Results are of practical relevance for decision makers, as they represent the most effective sequence of inspection works to be carried out based on the available funds. The proposed approach is demonstrated on a real large sewer system in the UK.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Determination of the minimum number of technological bases of a part

2020 ◽  
pp. 73-75
Author(s):  
B.M. Bazrov ◽  
T.M. Gaynutdinov
Keyword(s):  
Cost Price ◽  
Labor Input ◽  
Part Surface ◽  
Technological Base ◽  
Size Accuracy ◽  
Minimum Number ◽  
The Cost ◽  
Input Cost ◽  
Selection Of

The selection of technological bases is considered before the choice of the type of billet and the development of the route of the technological process. A technique is proposed for selecting the minimum number of sets of technological bases according to the criterion of equality in the cost price of manufacturing the part according to the principle of unity and combination of bases at this stage. Keywords: part, surface, coordinating size, accuracy, design and technological base, labor input, cost price. [email protected]

A Soft Hierarchical Process Approach for Decision Making in A Supply Chain

2015 ◽  
Vol 4 (1and2) ◽  
Author(s):  
Rajeev Dhingra ◽  
Preetvanti Singh
Keyword(s):  
Decision Making ◽  
Process Approach ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Conflicting Objectives ◽  
Realistic View ◽  
Hierarchy Process ◽  
Pair Wise Comparison ◽  
Supplier Selection Problem ◽  
Selection Of

Decision problems are usually complex and involve evaluation of several conflicting criteria (parameters). Multi Criteria Decision Making (MCDM) is a promising field that considers the parallel influence of all criteria and aims at helping decision makers in expressing their preferences, over a set of predefined alternatives, on the basis of criteria (parameters) that are contradictory in nature. The Analytic Hierarchy Process (AHP) is a useful and widespread MCDM tool for solving such type of problems, as it allows the incorporation of conflicting objectives and decision makers preferences in the decision making. The AHP utilizes the concept of pair wise comparison to find the order of criteria (parameters) and alternatives. The comparison in a pairwise manner becomes quite tedious and complex for problems having eight alternatives or more, thereby, limiting the application of AHP. This paper presents a soft hierarchical process approach based on soft set decision making which eliminates the least promising candidate alternatives and selects the optimum(potential) ones that results in the significant reduction in the number of pairwise comparisons necessary for the selection of the best alternative using AHP, giving the approach a more realistic view. A supplier selection problem is used to illustrate the proposed approach.

Pareto Set as a Model for Dispatching Resources in Emergency Centres (Preprint)

2018 ◽  
Author(s):  
Ricardo Guedes ◽  
Vasco Furtado ◽  
Tarcísio Pequeno ◽  
Joel Rodrigues
Keyword(s):  
Operational Research ◽  
Real Data ◽  
Pareto Set ◽  
Multi Objective Optimization ◽  
Pareto Dominance ◽  
Four Dimensions ◽  
Multi Objective ◽  
The Best Approximation ◽  
One Year ◽  
The Cost

UNSTRUCTURED The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.

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