Archive for category Optimization

Reducing Cost of Road Maintenance for the Resources Industry

production-1891426_640Haul road in open mine has short durability. It is because haul road is constructed without asphalt/concrete pavement and passed by big vehicle with heavy load. There is some kind of decreasing quality of haul road such as improper cross section, inadequate roadside drainage, corrugations, potholes, ruts, and loose aggregate. Poor haul road quality will impact on increasing production costs and decreasing mine productivity. Usually open mine use motor grader to maintain the quality of haul road. Way of working of motor grader is to scrap the inadequate haul road surface.

There are some differences among the haul road segments such as characteristic, traffic density, kind of decreasing quality, durability, etc. Therefore, systematically grader route and schedule is needed to minimize the delay of haul road maintenance. Usually grader route and schedule just based on grader’s operator experience. There is no specific approach that can be used in grader route and schedule.

This research focused on grader route and schedule optimization in coal haul road maintenance. Optimization model in this research is designed using Bandit Algorithm. The objective of the optimization model is to minimize the maximum penalty. In this case, penalty is used to describe amount of loss that is caused by maintenance delay on each haul road segment. Grader start from the initial point to a road segment and moves over and over to the other road segment until working hour is over. Determination of he next road segment is based on weight of maintenance delay on each road segment. Greater the weight of the maintenance delay of a road segment, greater the probability of that road segment to be addressed by grader. Grader scraps if the road segment is late maintained and just passes if otherwise. When the working hour is over, grader stops moving and optimization model calculates the objective and records the route as a new solution. The steps are done again as many as have been determined (iteration). Solution with the best objective is chosen as the final solution.

With the probability, grader is not directly addressed to the road segment with the greatest maintenance delay weight to allow for the other road segments to be the next grader destination. This is because short term solutions have effect on long-term solution (whole solution); maybe the best short-term solution is not the best long-term solution. An example in a simpler problem is: we must determine route from city A to city D with 2 possible route that are A-B-D and A-C-D. With the distance between A-B < A-C, A-B is the best first movement. But for the overall movement, maybe A-B-D is not the closest route. Although the distance between A-B < A-C, distance of A-C and C-D can be closer than A-B and B-D.

Optimization model showed a significant cost savings for the mining operations by creating a more effective roads maintenance with reduce cost. With the pressure of low prices in the resources industry, a simple but yet complex optimization can help them stay more competitive.

This research is conducted by Denni and Dr. Komarudin.


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This is What You Should Do When You Have No Doraemon’s Magical-Anywhere-Door

There are times when we wish Doraemon’s magical-anywhere-door really does exist. If so, we can reach our destination without having to travel miles in a long time. But, since Doraemon does not exist, fortunately there is something we can do to at least save the mileage and time we sacrificed to travel from one to another places. Especially in case of post men or delivery couriers who have to visit a lot of destinations in such limited amount of time and capability.

Recently, a research assistant from Systems Engineering, Modeling, and Simulation Laboratory from Industrial Engineering major, Universitas Indonesia is conducting a research about Vehicle Routing Problem with Time Windows to optimize distribution route and schedule. It was first inspired by Indonesia’s current logistic condition which is still not optimal. It is proven by the decreasing index of Indonesia’s logistic performance during the past five years. One of the reason is the high Indonesia’s logistic cost which can be considered as the highest logistic cost in the world. And the one that contributes almost half of the logistic cost is transportation cost.

On the other side, customer needs are rising annually. Moreover, the growing online shopping market create an increasing demand of same-day delivery service. Based on McKinsey survey, online retailers as the main originator of B2C shipments, have a large interest to reduce delivery time in order to foster the products sale. Therefore, we need a better planning of distribution route and schedule, especially for delivery service providers and courier companies.

The purpose of research conducted at SEMS Laboratory about Vehicle Routing Problem with Time Windows (VRPTW) is to find the most optimum distribution route with lowest total distance yet still manage to fulfill all demand and considering the constraints of vehicle capacity and customers’ time windows.

Since VRPTW belongs to NP-hard optimization problems, our researcher used heuristic method which is translated to Netbeans 8.1 software in C++ programming language. They also use local search to perform simple iterations to produce fairly accurate solutions. Local search methods which are used in this study are exchange, two-opt, and insert. They can be applied to customers in the same route (intra-route) and customers in different routes (inter-route). Basically, these methods perform some iterations of moves that determine the most optimum combination and sequence of customers to visit. This will be finalized by using Lin Kernighan Helsgaun algorithm. The iteration will stop once it can not generate a better solution.

Fig 1. Illustration of 2-opt intra-route move

Fig 1. Illustration of 2-opt intra-route move

The resulting improvements will ultimately result in reduced transportation costs. Thus, vehicle routing problem with time windows can be a solution for urban logistic problems. So, when you do not have any Doraemon’s magical door, make yourself sure that at least you have a well-planned distribution route and schedule!

This Research is Conducted by Vincencia Sydneyta and Dr. Komarudin

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How to optimize unequal area facility layout to maximize storage

work-1713103_640Facility layout problem, especially with the unequal departmental area (UAFLP), is one of the problems studied in combinatorial optimization and has received the attention of many researchers in the past decade. The goal of UAFLP is to allocate departments into a facility to obtain the most efficient arrangement. The UAFLP study has a final objective to minimize the total cost of material handling between departments.

Competition in today’s business world is inevitable. Increasing the quality of productivity becomes one of the keys to success in facing competition with business management effectively and efficiently. This can happen by maximizing existing resources ie employees, machines, and other facilities. Therefore, the industry needs to be able to optimize production capability and effectiveness to face competitors. The production process becomes the key that needs to be managed effectively to minimize production costs with higher effectiveness.

Facility layout design has a close reinforcement to the size of the physical arrangement of elements in a manufacturing and service system, such as department, machinery, operational tools, and so on. The purpose of the facility layout design is the design with the minimum material handling cost. With proper facility layout, material handling costs can be reduced. In general, material handling contributes about 20-50 percent of the total. Reduction in the company’s operational costs, along with the increased efficiency of the production system becomes a necessity that every industry needs to do.

The problem of facilities layout that is often the researcher’s attention is Unequal Area Facility Layout Problem (UAFLP). Initially, UA-FLP was developed by Armor and Buffa (1963). They explain that there is a rectangular facility with a fixed Width and Height and several (n) departments that need to be allocated to the facility. There are some problems that have not found the optimal solution and require a long computation time. The goal is to reduce non-feasible solutions to reduce the complexity of possible solutions.

This research will develop a mathematical model using Mixed Integer Programming method based on Flexible Bay Structure. Some additional constraint functions will be attempted to be added to the model. Testing is done by comparing the effect of each additional constraint function that has different approaches in cutting the complexity of possible solutions. The comparison result of the combination of the constraint function used indicates which constraint function has a major influence in reducing the computation time of the model.

This research concludes that all simulated problem sets using additional constraints in the model can provide better computation time than before. The effect that occurs can be the value of the solution becomes not optimum or remain optimum. All computational time gives significant improvement.

This research is conducted by Randa Adi Saputra and Komaruddin

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Multi-Period Maritime Logistics Planning for the Better Logistics Network Planning

It’s inevitable that the price of commodities in the eastern part of Indonesia is much higher than in the west. The unbalance economic growth between these two parts of Indonesia, might be one of the reason. Hence, the main trade activities happen mostly in the west, especially in Java island which could be called as the center of this country.

freighter-315201_640According to Meeuws and Bahagia, Indonesia as an archipelago country is dependent to maritime logistics on transporting goods and transportation. But unfortunately the performance of logistic in Indonesia is still poor. Also, the cost of logistics in Indonesia is still high. Until 2011, the cost of logistics is equal to 24.64% of Indonesia’s GDP.

Liner shipping company, as the provider of maritime logistics services, is looking for technology for optimizing their cost planning in operating and enhancing their fleets. The purpose of this plan is to make the capacity of their fleets matches the demand of container. The main goal for every company is of course to gain maximum profit. But the high of logistic cost and the unbalance trade activities in Indonesia might be the problem for liner shipping company to achieve that.

In liner shipping there are three different time-horizon levels. There are strategic level, tactical level, and operational level. The strategic level has the longest horizon and it involves determining the optimal fleet. The tactical planning level is done once in the several months and it involves constructing ship schedules. The shortest term decision level is the operational level. It involves determining the optimal allocation of cargo.

Previously there has been a research on Indonesia’s maritime logistic, especially in liner shipping made by Meijer and Van Rijn from Netherland. The purpose of their research is to gain maximum profit by optimizing liner shipping network design in Indonesia. But their research did not consider demand in the future (multi-period planning). Multi-period planning is crucial for liner shipping company in planning and developing the maritime logistics business.

SEMS researchers see this as an opportunity for our research. Therefore we make a research on multi-period liner shipping network design in Indonesia. The purpose is for the liner shipping company to gain maximum profit by optimizing their network design. In doing so, there are given conditions and scenarios in order to acknowledge which scenario suits best for multi-period planning. The outcome of this research is also to design the optimum logistics network which involves, which routes to be used, how many ships have to be allocated, and the cargo allocation.

This Research is conducted by Mellianna Fiannnita Purba, Komarudin and Armand Omar Moeis.

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SEMS Research Highlights 2015: Improving the Soekarno Hatta International Airport Utilization as the Main Gate of Indonesia

With the steady economic growth for the last ten years in Indonesia has made people mobility across the nation is at all time high. This is why, that most airport in Indonesia is operated more than its capacity. Soekarno Hatta International Airport (SHIA) is currently operated twice than its designed capacity. This problem has strong influence to the level of service of the airport, which next could lead to the decreasing of the passenger’s satisfaction (Yan, Shieh, & Chen, 2002). The challenges of the airport operator are to do further investment and to optimize the utilization of current ability.

Based on a research done by Redaksi Angkasa (2014), the current maximum traffic capacity of SHIA is 72 landing-takeoff traffics per one hour. They found that this still could be improved till 86 landing-takeoff traffics per one hour. Another standing point is more than 40% flights in SHIA is being parked in the remote area. The remote area is basically the aircraft parking area, located far away from the terminal building.

SEMS was trying to solve this problem, because we believe the better service from gated flights could maintain the image of SHIA as the main gate of Indonesia. There are some researches already studied about this topic. Bennel, Mesgarpour, & Potts (2011) have done a research focus on developing an optimization model. The objective of the study is to maximize the number of flights. Another research was done by integrating the runway allocation and gate assignment problem to maximize the number of flights could be accommodated in an airport (Nahry, T., & Y.J., 2013). Additionally, SEMS saw a research opportunity not to focus on operator’s perspective only, but also on the passenger’s perspective such as minimizing flight tardiness and minimizing passenger walking distance in the terminal.

This research is basically focusing on developing an optimization combination model of runway and gate assignment. The output of this research is to generate to most optimal runway and gate schedule concerns on 4 objectives, such as maximizing landing-takeoff traffics, minimizing flight tardiness, minimizing flights being parked in remote area, and minimizing passenger walking distance in airport. The model is done using the Genetic Algorithm Optimization Approach. The Genetic Algorithm it self is a metaheuristics algorithm, functioning to generate the best solution in a certain solution space of a certain problem.

Using the model, a significant reduction on un-gated flight has been achieved which reduce the traveling distance of the passenger.

This research is Conducted by Gede Arya Satya Dharma, Aziiz Sutrisno, Armand Omar Moeis, and Akhmad Hidayatno

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