26 MAR 2026 (THU) 10:30-11:30

Geography Distinguished Seminars Series

Ignoring the Obvious: what about close-to-optimal solutions in spatial optimization?

Date: 26 MAR 2026 (Thursday)

Time: 10:30-11:30 (HKT)

Venue: CLL, Department of Geography, 10/F, The Jockey Club Tower, Centennial Campus, HKU

Mode: Hybrid

Via Zoom: Zoom link will be provided upon successful registration

Registration link: https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=105920

---

Abstract:

In many applications of Operations Research to urban problems, researchers often overlook close to optimal solutions, when in fact they may be equivalent or even superior to what has been identified by an optimization model. There are several reasons why this is the case. First, analysts often search for the best solution to a model, while at the same time the model may not fully capture the true objective of the decision maker. Brill (1979) raised this issue in public sector applications, when he suggested that decision makers were often reticent to acknowledge all of their objectives in what might be a politically charged environment. Second, analysts in looking for that true optimal solution often neglect that the last small percentage of system improvement is often accomplished only when substantial changes must be made to a current solution. Brown, et al. (1997) argue that great solutions can often be accomplished when seeking a limited number of changes to a current solution. A third major issue is that the data that may be used in a project may be incomplete and contain errors. Overall, there are many reasons why one should explore solution space for close to optimal solutions. This paper explores solution exploration using two commonly used models in urban facility location and firmly demonstrates that solving only for the optimal solution to a given problem is foolhardy.

Professor Richard Church

Distinguished Professor Emeritus, Department of Geography, University of California

Professor Richard Church specialize in the analysis of problems defined over space and time, including logistics and transportation, location theory, water resource systems, and urban and environmental systems using and developing new techniques in Operations Research, GIS, Decision Theory, and Heuristics.

---