Anna Maria Sri Asih

Urban distribution center location: Combination of spatial analysis and multi-objective mixed-integer linear programming

Location of urban distribution center (UDC) has played an important role in reducing distribution cost, environmental impact, and traffic congestion in urban areas. The article aims at evaluating potential location of UDC for sugar commodity using a combined approach that comprises two stages: spatial analysis and multi-objective mixed-integer linear programming. Results demonstrate that different locations of UDC correspond to different costs and environmental implications. It is suggested that a new UDC for the sugar commodity can be located at the east part of the city outskirt. Using more than two UDCs in the studied case appears to be not economically and environmentally beneficial.

Comparison study of metaheuristics: Empirical application of delivery problems

Many existing studies have used hypothetical data to evaluate the performance of various metaheuristics in solving delivery route optimization. As empirical data impose characteristics of a particular problem, it is necessary to evaluate whether the problem characteristics may influence to the performance of metaheuristics. This article therefore attempts to compare the performance of metaheuristics, that is, genetic algorithm, ant colony optimization (ACO), particle swarm optimization, and simulated annealing (SA), to solve an empirical delivery problem in Yogyakarta, Indonesia. Two cases are developed to capture different characteristics of empirical data. The first case introduces delivery problem of one logistics operator and 58 retailers; the second case presents collaborative strategy in delivery problem, involving two logistics operators and 142 retailers. Results indicate that ACO and SA perform better with respect to less distance traveled for both cases and higher truck utility and lower number of routes for the second case.

Collaborative distribution - application to the city of Yogyakarta, Indonesia

Increasing of population leads to escalation of demand needs which results in busier logistics activities. Collaborative strategy has become an alternative to manage these activities, depending on the conditions in a certain location. This paper applied collaborative distribution model to Yogyakarta city, in order to see whether the collaboration is beneficial. The performance of collaborative distribution model is limited to the efficiency of capital and transportation cost based on optimum routing selection. In general, collaborative strategy showed more savings in total cost than that for the non-collaborative one. However, building and land investment should be an important consideration especially if collaborative strategy requires distribution centers expansion.

Simulasi aliran pasien rawat inap untuk mengurangi bottleneck

Bottleneck is possible to occur in a system like hospital, especially in admission and discharge of inpatient processes. It can have impact on increasing waiting time and delayed time. Some alternatives were proposed to reduce them, i.e. shift scheduling and human resource allocation. This research modelled real system accompanied by two scenarios: the first scenario was conducted by balancing human resource utility without altering number of employees, whereas the second scenario considered possibility of changing number of employees. The results showed that both scenarios produced reduction of waiting time and delayed time. The first scenario is more feasible compared to the second as no hiring or firing employees occurred, resulting in waiting time reduction of 110.6 minutes (15%) and decrease in delayed time by 184 minutes (15.9%). The reduction of waiting time and delayed time is higher in scenario 2, which are 423.6 minutes (57%) and 281 minutes (24%), respectively. However, there must be 4 additional employees hired in pharmacy applied in scenario 2.