Multi-objective Goal Programming Model Research Articles

A Stochastic Goal-Based Economic Order Quantity Model for Dairy Products

Resilient efforts are still sought to optimize the inventory of dairy products under demand uncertainty. Several industries operate under uncertainties that severely affect company performance. In this paper, a multi-objective goal programming model is proposed to optimize the economic order quantity of dairy products under stochastic demand. Adopting a Markov chain approach, the model initially defines the demand transition matrix, inventory cost matrix, objective function, priorities, and goal constraints of dairy products. The model seeks to minimize the deviation variables from the targeted economic order quantity and total inventory costs of dairy products over a finite period planning horizon. The sum of deviations is minimized so that the actual economic order quantity and inventory costs meet the targeted levels of dairy products. Using the simplex method, an analytical solution is obtained and a numerical example is presented for illustration; demonstrating the overachievement or underachievement of the targeted economic order quantity and inventory costs of dairy products. Results indicate how priority-based goal programming solution is sensitive to the highest priority to be achieved. The proposed model can be effective where the relevant economic order quantity and inventory costs can be prioritized if necessary.

Determining the optimal strategy for aggregate production planning (APP) during the Covid-19 crisis using an algorithm Harmony Search Algorithm

Determining the optimal strategy for aggregate production planning (APP) during the Covid-19 crisis using an algorithm Harmony Search Algorithm

Optimal Allocation of Gas Resources to Different Consumption Sectors Using Multi-Objective Goal Programming

Natural gas is a main source of energy in Iran, and optimal allocation to different sectors is crucial, based on realities, geopolitical considerations, and national security concerns. In this paper, a multi-objective goal programming model is developed to study the optimal allocation of this resource to various consumption sectors, including household business, industry, petrochemical industry, power plants, injection to oil fields, and export from Iran for the horizon of 2025. In this research, the energy security index is prioritized over other indicators. Two objective functions are considered: the first is maximizing the energy security index (minimizing the cost of energy security), and the second is minimizing the relative weight of different consumption sectors. The goal share of the various gas sectors, the amount of consumption of the various consumption sectors, and the allocatable and predicted amount for each year is calculated. Household business, power plants, petrochemical industries, industry, and export aid injection to oil fields are the most consuming sectors in 2025, respectively. Also, based on cost minimization, power plants, petrochemical industries, and industries in general are the more consuming sectors, respectively.

Multi-objective optimization modelling for analysing sustainable development goals of Nigeria: Agenda 2030

Sustainability of developmental goals remains the significant challenges for every nation in the world. In an environment of flexibility coupled with multiple and conflicting objectives on social economic, energy and environmental issues, a fuzzy goal programming approach proves to be suitable in helping policymakers for attaining their aspirational goals as it takes imprecise information into account. In this study, we proposed a multi-objective goal programming model to analyse the socio-economic, environmental and energy sector of Nigeria. The sectors relating to the gross domestic product, electricity consumption, employment and greenhouse gases emissions are regarded as the key sustainable development goals (SDGs) for the year 2030, upon which all other goals depend on directly or indirectly. We considered four scenarios based on decision-makers' value judgments using the analytic hierarchy process (AHP). Moreover, we have developed a weighted fuzzy goal programming model for the SDGs incorporating the AHP. The model reveals that individual goals are achievable at 81, 83, and 89 per cents, respectively, while the overall achievement function indicated only 73 per cent achievement is possible. The optimal employment for the various economic sectors is also computed at various tolerance values and presented alongside Pareto objective values. The results yielded an economic justification mathematically and provided insight for critical and future strategic planning towards achieving sustainable economic policies. The models can be replicated in the context of other nations in addressing long-term socio-economic planning and indispensable requirements for renewable sources inclusion to satisfy future energy demand economically without environmental damages.

“Qualitative Analysis to Assess the Best Renewable Energy Scenario for Sustainable Energy Planning”

Rural population in developing nation is having limited access to the clean and modern energy sources. Rural poor in India are mostly dependent on electricity, fire wood, dung, and biomass for their domestic energy need. Due to the dependence on conventional energy sources pollution and rural health are the issue of concern which directly affect on the national productivity. Ministry of New and Renewable Energy of the Government of India giving stress to intensify the energy supply and modern sources of energy to rural area up to normal consumption level through renewable energy sources The aim of the present study is to determine the best renewable energy scenario for sustainable development of rural area. For this aim, author used both quantitative and qualitative analysis technique to determine the best energy scenario for application. For quantitative analysis multi objective goal programming model is used and the result obtained by it validated with multi-attribute decision making approach. The present work specifically focused on Analytic Hierarchy Process (AHP) methodology. In the proposed method, the weights of the selection criteria are determined by pair-wise comparison matrices of the AHP. Results indicate that Cost Employment Generation Scenario (CEGS) is the most appropriate renewable energy option.

A system dynamics approach to planning and evaluating interventions for chronic disease management

Studies have been reported on the applications of systems science to chronic disease management, but few, if any, have concentrated on chronic kidney disease (CKD). We examined the impact of a system dynamics approach to the evaluation of interventions in care of patients with CKD. We developed a stock flow simulation model and a multi-objective goal programming model. After calibrating the model, eight scenarios were analysed to measure intervention effects. Physician education (PE) had the most significant impact on reducing disease progression rate (DPR) from Stage 3 to Stage 4, while care coordination had a substantial impact on decreasing DPR Stage 4 to Stage 5. The addition of either CME or primary care team building to PE led to significant reductions in DPR for patients with Stage 3 CKD. The goal programming model indicated that a growing number of primary care physicians and care managers are needed to manage CKD patients overtime. This study showed that the stock flow model is a potentially powerful tool for supporting informed decision-making for planning and implementing interventions at various phases.

A fuzzy multi-objective goal programming model for solving an aggregate production planning problem with uncertainty

The aggregate production planning problem is one of the well-known planning problems in industries and manufacturing systems. It is implemented at an aggregated level without the need to provide detailed information about material and resource requirements for individual products. A multi-objective aggregate production planning problem is studied in current paper with four criteria, namely: 1) shortage and inventory; 2) overtime and idle time; 3) manpower level; 4) currency saving in a mid-term planning horizon. After describing the problem, a goal programming model is presented to formulate the problem mathematically and then a fuzzy goal programming model is utilised to encounter the uncertainties encountered in real-world systems. Unlike many previous works, this paper proposes a linear programming model which is solvable in a short time. Finally, to evaluate the performance, both models are verified with real data.

A fuzzy multi-objective goal programming model for solving an aggregate production planning problem with uncertainty

The aggregate production planning problem is one of the well-known planning problems in industries and manufacturing systems. It is implemented at an aggregated level without the need to provide detailed information about material and resource requirements for individual products. A multi-objective aggregate production planning problem is studied in current paper with four criteria, namely: 1) shortage and inventory; 2) overtime and idle time; 3) manpower level; 4) currency saving in a mid-term planning horizon. After describing the problem, a goal programming model is presented to formulate the problem mathematically and then a fuzzy goal programming model is utilised to encounter the uncertainties encountered in real-world systems. Unlike many previous works, this paper proposes a linear programming model which is solvable in a short time. Finally, to evaluate the performance, both models are verified with real data.

Multi-objective analysis for assessing simultaneous changes in regional spinal curvatures under backpack carriage in young adults

Change in sagittal spinal curvature from the neutral upright stance is an important measure of the heaviness and correctness of backpack use. As current recommendations, with respect to spinal profile, of backpack load thresholds were based on the significant curvature change in individual spinal region only, this study investigated the most critical backpack load by assessing simultaneously the spinal curvature changes along the whole spine. A motion analysis system was used to measure the curvature changes in cervical, upper thoracic, lower thoracic and lumbar regions with backpack load at 0, 5, 10, 15 and 20% of body weight. A multi-objective goal programming model was adopted to determine the global critical load of maximum curvature change of the whole spine in accordance with the maximum curvature changes of the four spinal regions. Results suggested that the most critical backpack load was 13% of body weight for healthy male college students.Practitioner Summary: As current recommendations of backpack load thresholds were based on the significant curvature change in individual spinal region only, this study investigated the backpack load by considering simultaneously the spinal curvature changes along the whole spine. The recommendation, in terms of the global critical load, was 13% of body weight for healthy male college students.

Multi-objective optimization model for water resource management: a case study for Riyadh, Saudi Arabia

A multi-objective goal programming model was developed for water distribution from multiple sources to multiple users. The model was applied in Riyadh, Saudi Arabia, for the period of 2015–2050. In Riyadh, water sources are groundwater (GW), desalinated water (DW) and treated wastewater (TWW), while the users are domestic, agricultural and industrial sectors. The model was applied to: (1) satisfy water demands and quality; (2) maximize TWW reuse and GW conservation; and (3) minimize overproduction of DW and overall cost. In 2015, the required allocations of GW, DW and TWW are 3286, 662 and 609 MCM, respectively, which are projected to be 4345, 1554 and 1305 MCM in 2050, respectively. GW source is likely to satisfy the predicted withdrawal of GW till 2035, while probabilities of non-satisfaction of full demands of GW in 2040, 2045 and 2050 were 0.04, 0.23 and 0.51, respectively. Supply of DW and reuse of TWW are needed to be increased to satisfy the predicted quantities during 2015–2050.

A Multi-Objective Model for Fire Station Location under Uncertainty

The efficient location of fire stations may involve multiple objectives, some of which are possibly conflicting. A multi-objective goal programming model is proposed in this paper taking both service quality, setup costs, and operating costs into consideration in the uncertain environment. Based on uncertainty theory, an equivalent deterministic programming model is developed at a given confidence level of safety requirement. A numerical example is presented as well for illustration.

Production planning in a machine tool company: application of a linear lexicographic goal programming approach

This paper describes a multi-objective goal programming (MOGP) model that has been developed for a machine tool manufacturing industry to find the optimum production plan as a means to know what products to be considered and how much to be produced. Performance criteria such as gross profit, product quality, machine utilisation, production cost and work-in-process (WIP) inventory were identified as multi-objectives. Lexicographic goal programming modelling approach was applied to solve the proposed multi-objective model. In order to demonstrate the capability of the developed linear MOGP model, a pre-emptive goal priority structure has been formulated in consultation with the company. The sensitivity of the MOGP model was tested with respect to alterations in the order of goal priorities and changes in parameter values. The insights gained from the sensitivity analysis will assist the similar companies to find out an optimal level of production activities on par with the organisational goals.

Application of physical system theory and goal programming to modelling and analysis of waste management in national planning

Abstract Conventionally, national planning models have emphasized two major interfaces of the economic system, i.e. the input, and the output. The third important interface, i.e. waste, has not received the attention it deserves in the economic planning process. Attempts to include waste parameters in economic environmental modelling has been limited to tackling certain environmental considerations in national planning. The broader perspective of waste management (WM) has, by and large, been ignored in most of the literature in this context. This paper presents a graph theoretical system model of a multi-sectoral national economy including WM sectors. The system model of the economy has been integrated to a multi-objective goal programming model to fulfil the WM goals in a particular planning period. The model takes care of a variety of factors like resource structure, standard of living, sustained economic growth, waste recycling, environmental quality, etc. The model may be applied to determine the opti...

An intermodal investment decision model in the transport sector

Transport investment decision-making at government level has acquired special importance in recent years because of rising costs and greater involvement of government in the transport system, especially in developing economies. In the present paper a multiobjective optimization model is presented for intermodal transport investment at the national level and is tested for the Indian transport sector. The novelty of the modeling approach is the combination of a number of single objective linear programming models into a multiobjective goal programming model. An analysis of the LGP results indicate that for the Indian transport sector, the railways and the marine transport systems should receive higher shares of planned investments compared to their current allocations.