Sharif Digital Repository

This thesis investigates the scheduling of television advertisements, which is critical for optimizing the efficiency and profitability of marketing campaigns for TV networks. Since its inception in the 1930s, television has been a cornerstone of advertising, enabling businesses to reach broad and diverse audiences. The evolution of TV advertising strategies, particularly with the rise of digital media competition, underscores the importance of effective advertisement scheduling to maintain relevance and effectiveness. To address this challenge, a comprehensive mixed-integer linear programming (MILP) model was developed. This model incorporates various hypotheses to manage real-world... 

In recent years, data-driven planning and analysis in political institutions, particularly legislative bodies, have gained significant importance, leading to enhanced decision-making processes and policy effectiveness. Due to their high transparency and direct impact on macro-level political decisions, these institutions are recognized as one of the most critical research domains in this field. In this study, considering the complex and unique structure of legislative processes in parliaments and senates, a mixed-integer programming model was designed to prioritize the scheduling of high-impact legislative proposals. Given the inefficiency of exact solution methods in large-scale problems,... 

The Emergency Department is one of the most important departments in a hospital, which is continuously active and plays a crucial role in saving patients' lives. For this reason, using research methods in operations and optimization can greatly help improve the performance of the Emergency Department. In this thesis, the emergency scheduling problem is examined with the objective function of minimizing the total weighted sum of job completion times, considering the random nature of service times. Since the objective function of the problem is to minimize the total job completion time, the job completion time is obtained as the sum of several random variables. Considering the additivity... 

In today’s highly competitive industrial landscape, where escalating raw material costs and constraints on production resources impose significant operational pressures, improving productivity and minimizing operational expenditures have emerged as critical imperatives for manufacturing enterprises. This research proposes the formulation and implementation of a sophisticated mathematical optimization model, structured as a Mixed-Integer Programming (MIP) framework, to address the complexities of multi-product production planning within the motor oil packaging industry. The focal organization in this study is confronted with numerous operational inefficiencies, including constrained warehouse... 

Mass casualty incidents (MCIs) specifically refer to events in which a large number of individuals are injured or killed. These incidents may include traffic accidents, natural disasters, or other critical situations that require immediate emergency services to save lives. In such circumstances, the rapid and optimal management of emergency resources—particularly ambulance dispatch and patient allocation to hospitals—can significantly increase the chances of survival. One of the key challenges in these scenarios is the effective scheduling and dispatching of ambulances. In general, casualties are divided into two categories: emergency patients who require immediate treatment, and... 

In recent decades, the rapid growth of global trade, the increase in ship capacity, and the pressure to comply with environmental regulations have created complex challenges for container terminals. One of the key issues in managing these terminals is the optimal scheduling of quay cranes, which plays a critical role in reducing vessel waiting times, improving operational efficiency, and lowering pollutant emissions. This study proposes an integrated optimization model for quay crane scheduling in a continuous berth, combined with preventive maintenance planning. A distinctive feature of the proposed model is its simultaneous consideration of environmental factors and physical operational... 

Emergency medical services (EMS) face critical challenges in ambulance dispatching for optimizing response times, especially under multiple sources of uncertainty such as stochastic travel times and on-scene durations. Traditional dispatch policies—e.g., assigning the first available ambulance or the least-loaded unit—struggle to manage these uncertainties and often underperform in high-demand, highly variable settings. This study proposes a data-driven optimization framework for dispatch that rests on three pillars: (i) context-conditioned, data-driven scenario generation that learns conditional distributions and inter-variable dependencies; (ii) a two-stage robust optimization model... 

This thesis models and solves a time-dependent generalized pollution-routing problem with explicit social considerations. The objective is to balance total operating cost and pollutant emissions while maintaining schedule regularity. We propose an integrated framework that jointly determines routing, departure times, and cruising speeds and evaluates solution quality through academically established Pareto-front indicators. For small instances, a mixed-integer linear programming formulation is developed and solved exactly with commercial optimizers. For medium and large instances, two metaheuristics are employed, namely a genetic algorithm based on NSGA-II and a multi-objective ant colony... 

The tourism industry stands as one of the most pivotal sectors in the modern global economy, with hotels constituting one of its largest components. Concurrently, hotel management represents one of the most significant commercial activities worldwide. Among the crucial responsibilities of hotel management is the challenge of room allocation to guests seeking accommodation. In this study, we investigate the problem of assigning hotel rooms to guests. To achieve this, we first collect reservation requests from guests and execute the allocation process based on these requests. This procedure is facilitated through mathematical modeling with the objective of maximizing the number of accepted... 

We examined the Phase-Type distribution to calculate project activity duration and solve the resource constraint project scheduling problem with non-deterministic activity duration through meta-heuristic techniques. The activity usually doesn't have a fixed duration. The problem is caused by numerous factors that exist when carrying out a project, such as a lack of resources, late delivery of resources, and mistakes made by people. The literature review revealed that the scheduling problem had been thoroughly researched. The more accurate and realistic the activity duration estimates, the better the project planning and cost control. For this purpose, in this research, the duration of the... 

According to the growing population and the need to make optimal use of available resources, the discussion of planning and scheduling in healthcare will be useful. One of the most expensive and lucrative sections in a hospital, which always spends a large percentage of renewable and non-renewable resources, is the Operating rooms (ORs). These ORs are the most important part of the hospital in terms of health and financial issues. In these scheduling problems, in order to be able to model the real situation, we needed to consider the recovery section integrated with the ORs. Also, the duration of surgery and stay in the recovery rooms are considered stochastic. In this study, we solve the... 

Surgery theaters are one of the most important and expensive departments in hospitals. Since the operating theaters are connected with other departments, improving the efficiency in the operating theaters can affect other departments as well, so effective and efficient planning and scheduling of the operating theater It is necessary. In this research, we study and investigate the problem of planning and scheduling surgery theaters under the uncertainty of surgery duration, considering the open scheduling strategy and having the list of patients and limited resources after surgery. Let's say that the parameter of the duration of surgery is uncertain and we have little data about it. Some... 

The blood supply chain faces substantial challenges due to fluctuations in donation and demand, as well as the perishability of blood products. Consequently, decision makers require an integrated analytical framework to ensure resilient and efficient operations. This study develops a multi-product, bi-objective robust optimization model for designing a blood supply chain capable of withstanding demand variability. From the perspective of blood bank managers, the model simultaneously minimizes operational costs and transportation time while satisfying hospital demand. The decision scope includes locating and configuring permanent and temporary facilities, determining shipment policies, and... 

In airlines, the problem of ‘flight crew scheduling’, as a part of the organization resources, holds great importance. Furthermore, considering the numerous and specific regulations regarding the working hours of flight crew, as well as constraints resulted by origin, destination, and time of each flight, this problem is also highly complex. The most significant challenge in solving this problem lies in the “construction and selection of the crew pairings” In this research, first, according to the literature, definitions and regulations necessary for the problem are stated. Then the problem is modeled as a "set covering problem," in which the rows of the problem correspond to flights which... 

This research investigates permutation flow shop scheduling problems with sequence-dependent setup times with minimizing the number of tardy jobs as criterion (Fm|prmu, Sijk|ΣUj). A mixed integer linear programming model has been developed for the research problem. As the problem is shown to be NP-hard, several meta-heuristic algorithms based on tabu search (TS) and imperialist competitive algorithm are developed to heuristically solve the problem. In order to find the best meta-heuristic algorithm, random test problems, ranging in size from small, medium, to large are created and solved by the meta-heuristic algorithms. Then, a detailed statistical experiment, based on split-plot design is... 

Software Reuse, the use of (pre)existing artifacts to create new systems, can reduce development costs and improve software quality and productivity. With a primary investment, Software Product Line facilitates a systematic reuse of the common parts of an specific domain in developing similar systems of that domain. On the Contrary, Agile Methods who value working software over comprehensive documentations and such investments is not done, lack reuse in developing similar systems. Here the question arises: why do we completely or almost miss such reuse when the only focus is on creating working software? When such investments or additional works like documentation are not done? Is there any...